What Is the Difference between Quoted Spread and Effective Spread in an RFQ?

Concept

An institutional trader’s primary mandate is to translate strategic allocation decisions into executed positions with maximum fidelity and minimal cost. Within the architecture of a Request for Quote (RFQ) protocol, the distinction between the quoted spread and the effective spread is a fundamental measure of that translation’s efficiency. The quoted spread is the theoretical cost of immediacy, a static snapshot of the market’s price for liquidity offered by a dealer at a single point in time. It is the visible, advertised price differential between the bid and the ask.

In contrast, the effective spread is the realized, true cost of the transaction. It measures the distance between the final execution price and the prevailing market midpoint at the moment of the trade. This second metric captures the dynamic reality of execution, including any price improvements or slippage that occur within the RFQ process. Understanding this difference is core to building a robust execution framework.

The quoted spread is the dealer’s advertised price for liquidity; the effective spread is the actual price the institution paid.

What Defines the Quoted Spread in an RFQ?

The quoted spread is the foundational pricing signal within any quote-driven market structure, including the bilateral price discovery process of an RFQ. When an institution sends a request for a price on a specific instrument, each responding dealer provides a two-sided market ▴ a bid price at which they will buy and an ask price at which they will sell. The quoted spread is simply the difference between that specific dealer’s ask and bid prices (Ask – Bid).

This figure represents the dealer’s gross potential revenue for facilitating the trade, compensating them for the risks they undertake, which primarily include inventory risk and adverse selection risk. In the context of an RFQ, an institution might receive multiple quoted spreads from different dealers, each representing a distinct and competitive offer for the same block of risk.

This metric is a static signal. It reflects the dealer’s pricing model and risk appetite at the precise moment the quote is generated. It does not, however, guarantee the final execution cost.

It is an initial data point, a critical input into the trader’s decision-making matrix, but it is not the outcome itself. The tightness of the quoted spread is often perceived as a proxy for a dealer’s competitiveness, yet it is an incomplete measure of execution quality when viewed in isolation.

The Systemic Importance of the Effective Spread

The effective spread provides a more complete and actionable measure of execution cost. Its calculation is centered on the midpoint of the national best bid and offer (NBBO) at the time of the trade, which serves as a proxy for the instrument’s true underlying value. The formula is typically expressed as ▴ 2 |Execution Price – Quote Midpoint|. For a buy order, this measures how far above the midpoint the execution occurred.

For a sell order, it measures how far below. A lower effective spread signifies a better execution price, closer to the prevailing market consensus. This metric is profoundly important because it accounts for price improvements ▴ instances where a dealer executes a trade at a price more favorable than their own quoted price, or even inside the best publicly displayed quotes. In the competitive, multi-dealer environment of an RFQ, dealers are incentivized to offer such improvements to win flow. The effective spread captures this benefit directly, providing a precise measure of the value added during the negotiation and execution phase.

Strategy

Moving from concept to strategy requires viewing spreads as more than just post-trade metrics. They are dynamic data streams that inform an institution’s entire liquidity sourcing and dealer management strategy. A sophisticated trading desk does not simply observe these spreads; it weaponizes them to systematically reduce transaction costs, manage information leakage, and build a more resilient execution architecture. The strategic interplay between the quoted and effective spreads reveals the hidden efficiencies and frictions within the RFQ workflow.

Deconstructing the RFQ Timeline and Spread Dynamics

The lifecycle of an RFQ can be mapped against the evolution of these two spread metrics. The process begins with the submission of the request, which signals trading intent to a select group of liquidity providers. The immediate response is a set of competing quoted spreads. The strategic objective at this stage is to solicit the tightest possible quoted spreads without revealing too much information to the wider market.

The difference between the tightest quoted spread and the final effective spread is where the execution strategy proves its value. A positive outcome is one where the effective spread is narrower than the best quoted spread, an event known as price improvement. This delta is the quantifiable result of dealer competition and the trader’s skill in managing the auction process.

Effective spread analysis transforms execution from a simple action into a strategic, data-driven process for optimizing dealer relationships.

A negative outcome, where the effective spread is wider than the quoted spread, indicates slippage. This can occur in fast-moving markets where the midpoint moves against the trader between the time of the quote and the execution. A systematic analysis of this delta across all trades provides a powerful feedback loop for refining the RFQ process, such as shortening the time allowed for responses or adjusting the size of the requested blocks.

How Do Spreads Inform Dealer Selection and Performance?

An institution’s panel of liquidity providers is a strategic asset. Analyzing spread data is the primary mechanism for managing and optimizing this asset. By systematically capturing and comparing quoted and effective spreads for every RFQ, a trading desk can move beyond relationship-based dealer selection to a quantitative, performance-based model.

• Consistency of Quoting ▴ A dealer who consistently provides tight quoted spreads is valuable, but only if those quotes are actionable and lead to favorable executions. Tracking the hit rate ▴ the percentage of times a dealer’s tight quote wins the trade ▴ is a key performance indicator.
• Magnitude of Price Improvement ▴ The most valuable dealers are often those who provide the greatest price improvement. A desk should track the average difference between a dealer’s quoted spread and the final effective spread on trades they win. A dealer who quotes slightly wider but consistently delivers significant price improvement may be a more valuable partner than one who quotes aggressively but never improves.
• Adverse Selection Protection ▴ A dealer’s willingness to quote tight spreads in volatile or illiquid conditions is a measure of their risk appetite and commitment. Analyzing how a dealer’s quoted spreads widen during periods of market stress can help a trader understand which partners provide reliable liquidity when it is most needed.

This data-driven approach allows an institution to tier its dealers based on empirical performance, directing more flow to those who provide the best all-in execution quality. It transforms the dealer relationship from a simple counterparty arrangement into a performance-managed partnership.

Comparative Analysis of Spread Metrics

To fully integrate these metrics into a strategic framework, it is useful to compare their characteristics and what they reveal about the execution process.

Execution

The execution phase is where theoretical costs are crystallized into actual profit or loss. For an institutional desk operating at scale, the precise calculation and systematic analysis of spreads are not academic exercises; they are core components of a high-performance trading system. Integrating this analysis into the operational workflow requires robust data capture, clear formulas, and a commitment to using the output to drive continuous improvement.

The Mechanics of Spread Calculation

To execute a transaction cost analysis (TCA) program centered on RFQ flow, an institution’s trading system must capture several key data points for every trade ▴ the timestamp of the request, all dealer quotes (bid and ask), the timestamp of the execution, the executed price, and the executed quantity. Additionally, it must have access to a reliable feed of the consolidated market quote (NBBO) to establish the prevailing midpoint. With these inputs, the calculations are straightforward.

1. Quoted Spread Calculation ▴ For each dealer response, the formula is simply ▴ Quoted Spread = Dealer Ask Price – Dealer Bid Price. This should be calculated for every quote received to build a complete picture of the competitive landscape for that specific RFQ.
2. Quote Midpoint Calculation ▴ The reference point for the effective spread is the midpoint of the consolidated market quote at the time of trade execution. The formula is ▴ Quote Midpoint = (National Best Bid + National Best Ask) / 2.
3. Effective Spread Calculation ▴ This measures the total cost paid relative to the market midpoint. The universal formula is ▴ Effective Spread = 2 Direction (Execution Price – Quote Midpoint), where ‘Direction’ is +1 for a buy and -1 for a sell. This ensures the result is always a positive value representing the cost.
4. Price Improvement Calculation ▴ This quantifies the value added by the dealer relative to the best available public quote. For a buy order, the calculation is ▴ Price Improvement = (National Best Ask – Execution Price) Quantity. For a sell order, it is ▴ Price Improvement = (Execution Price – National Best Bid) Quantity. A positive result indicates a financial benefit to the institution.

Case Study a Multi Dealer RFQ for an Options Block

Consider an institution looking to buy 500 contracts of an ETH call option. The NBBO for this option is $10.00 bid / $10.20 ask, making the quote midpoint $10.10. The institution sends an RFQ to four dealers and receives the following responses. The trader executes the full block with Dealer C.

In this execution, Dealer B offered the tightest quoted spread ($0.20), identical to the NBBO. However, the trade was awarded to Dealer C, who, despite a wider quoted spread of $0.24, provided an execution at $10.18. The effective spread for this trade was 2 ($10.18 – $10.10), which equals $0.16. This is significantly better than Dealer C’s own quoted spread and also better than the best quoted spread from Dealer B. The institution received a price improvement of $0.02 per contract ($10.20 NBBO Ask – $10.18 Execution Price), for a total savings of $1,000 on the block.

This case study demonstrates that the tightest quoted spread is not the definitive factor. The final effective spread is the true measure of execution quality, and the ability to achieve price improvement is the hallmark of a successful execution strategy and a high-quality liquidity provider.

Reflection

Architecting Your Execution Intelligence

The analysis of quoted and effective spreads provides the foundational data for an institution’s execution intelligence system. The metrics themselves are simple, yet their strategic application is what separates a reactive trading desk from a proactive one. The data allows for a continuous feedback loop where execution performance informs dealer selection, and dealer competition refines execution quality.

The ultimate objective is to build an operational architecture that is self-optimizing, one where every trade generates not just a position, but also valuable data that hardens the system for the future. How does your current execution framework capture, analyze, and act upon the critical information embedded within these spreads?