# Can a Model-Derived Price Serve as a Sufficient Benchmark for Best Execution in the Absence of Quotes? ▴ Question

**Published:** 2025-08-09
**Categories:** Question

---

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![A multi-layered, circular device with a central concentric lens. It symbolizes an RFQ engine for precision price discovery and high-fidelity execution](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine-for-precision-execution.jpg)

## Concept

The question of whether a [model-derived price](https://prime.greeks.live/area/model-derived-price/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) can serve as a sufficient benchmark for [best execution](https://prime.greeks.live/area/best-execution/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) in the absence of quotes strikes at the heart of a fundamental tension in modern finance. It pits the regulatory and fiduciary imperative for demonstrable fairness against the operational reality of trading in markets where liquidity is ephemeral or non-existent. The answer, from a systemic perspective, is that a model-derived price is a necessary, and indeed critical, component of the best execution process, but its sufficiency is entirely dependent on the robustness of the framework within which it is used. It is an input, not a final verdict.

Best execution, as defined by regulators like FINRA, is not the achievement of the single best possible price, but rather the diligent application of a process designed to achieve a result that is as favorable as possible for the client under the prevailing market conditions. This distinction is paramount. It shifts the focus from an unattainable theoretical price point to a defensible and repeatable operational procedure.

In liquid markets, this procedure is anchored by a wealth of readily available data, primarily the National Best Bid and Offer (NBBO) for equities, and a competitive stream of quotes from multiple dealers in other asset classes. These external, verifiable data points form the bedrock of any best execution analysis.

The challenge arises when these external anchors disappear. For certain fixed-income securities, complex derivatives, or large blocks of less-traded equities, the market is not a continuous stream of prices but a collection of disparate, often latent, pools of interest. In these “Level 2” and “Level 3” asset classes, a “mark-to-market” valuation is impossible; one must “[mark-to-model](https://prime.greeks.live/area/mark-to-model/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).” This is the point where the model-derived price becomes the primary reference point.

Its function is to create a reasonable, quantitatively derived estimate of value where the market itself provides none. This provides a crucial starting point for any subsequent trading activity.

> A model-derived price acts as a foundational estimate of fair value, creating a verifiable reference point in markets devoid of continuous, actionable quotes.

However, relying on this price in isolation is a critical failure of operational design. The SEC’s guidance on [fair value](https://prime.greeks.live/area/fair-value/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), particularly for registered funds, underscores that a “good faith” determination of value is a procedural exercise, overseen by a board or a designated valuation committee. This same principle of procedural integrity applies directly to best execution. The model price is the first step, providing a calculated baseline.

The sufficiency of this benchmark is then established by the subsequent steps a firm takes to test, corroborate, and document its execution strategy in relation to that baseline. The model does not absolve the firm of its duty; it equips the firm to begin fulfilling it.

![A precision mechanical assembly: black base, intricate metallic components, luminous mint-green ring with dark spherical core. This embodies an institutional Crypto Derivatives OS, its market microstructure enabling high-fidelity execution via RFQ protocols for intelligent liquidity aggregation and optimal price discovery](https://options.greeks.live/wp-content/uploads/2025/08/institutional-crypto-derivatives-rfq-engine-high-fidelity-execution.jpg)

![A transparent, blue-tinted sphere, anchored to a metallic base on a light surface, symbolizes an RFQ inquiry for digital asset derivatives. A fine line represents low-latency FIX Protocol for high-fidelity execution, optimizing price discovery in market microstructure via Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-rfq-protocol-sphere-high-fidelity-execution-gateway.jpg)

## Strategy

![A complex, reflective apparatus with concentric rings and metallic arms supporting two distinct spheres. This embodies RFQ protocols, market microstructure, and high-fidelity execution for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine-3.jpg)

## A Framework for Defensible Execution

Developing a strategy for best execution in quote-less markets is an exercise in architectural design. The objective is to construct a system that is both operationally effective and regulatorily defensible. A model-derived price serves as the foundation of this structure, but its stability depends entirely on the pillars of process, validation, and documentation built around it. The strategy is not merely to generate a price, but to build a comprehensive valuation and execution workflow that acknowledges the inherent uncertainty of illiquid markets.

The first strategic decision involves the selection and implementation of the valuation model itself. The choice of model is dictated by the nature of the instrument. Methodologies can range from discounted cash flow (DCF) analysis for certain debt instruments to more complex approaches involving comparable securities or even option-pricing models to quantify illiquidity discounts.

The key is that the chosen methodology must be appropriate for the asset and, crucially, consistently applied. A firm’s policies and procedures must clearly outline which models are used for which asset types and under what specific circumstances.

![An intricate, transparent cylindrical system depicts a sophisticated RFQ protocol for digital asset derivatives. Internal glowing elements signify high-fidelity execution and algorithmic trading](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-protocol-architecture.jpg)

## Model Selection and Hierarchy

A robust strategy establishes a clear hierarchy of valuation techniques. This ensures that the most reliable methods are prioritized and that the level of subjectivity is understood and documented. The framework, often aligned with [ASC 820](https://prime.greeks.live/area/asc-820/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) for fair value measurement, provides a structured approach.

| Valuation Tier | Methodology | Primary Use Case | Key Inputs | Limitations |
| --- | --- | --- | --- | --- |
| Tier 1 | Matrix Pricing | Corporate or municipal bonds with no direct market, but with similar actively traded securities. | Yield curves, credit spreads, and prices of comparable bonds. | Dependent on the quality and true comparability of the reference securities. |
| Tier 2 | Discounted Cash Flow (DCF) | Non-transferable loans, private debt, or instruments with predictable cash flows. | Projected cash flows, discount rate, and credit default assumptions. | Highly sensitive to assumptions about future cash flows and the discount rate. |
| Tier 3 | Comparable Transactions | Private equity, venture capital, or unique assets with recent transaction history. | Price of recent investment rounds, M&A multiples from similar companies. | Past transactions may not reflect current market conditions. |
| Tier 4 | Asset-Based Valuation | Asset-backed securities or holding companies. | Fair value of underlying assets and liabilities. | Does not capture intangible value or future growth prospects. |

![Two interlocking textured bars, beige and blue, abstractly represent institutional digital asset derivatives platforms. A blue sphere signifies RFQ protocol initiation, reflecting latent liquidity for atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-for-prime-os-execution.jpg)

## The Human Element in the System

A critical component of the strategy is acknowledging the model’s limitations and integrating human judgment in a structured way. The output of a model is a theoretical price. The execution of a trade, however, must consider factors that a model cannot easily quantify ▴ the size of the order, the potential for market impact, the urgency of the trade, and the creditworthiness of available counterparties. This is where the system must mandate a “factors analysis.”

> The strategy must treat the model’s output not as an answer, but as a calibrated instrument to be used by a skilled operator.

This involves creating a formal process, often managed by a best execution or valuation committee, to review the model-derived price in the context of the specific trading scenario. It is within this forum that the intellectual grappling truly occurs. The committee must weigh the model’s price against the qualitative execution factors. For instance, a trader might justify executing a large block order at a price slightly inferior to the model’s output to avoid the significant market impact that would result from trying to achieve the theoretical price.

Conversely, a price significantly better than the model might be achievable due to a unique, non-obvious liquidity opportunity. The strategy must not only allow for these deviations but require that their rationale be rigorously documented. This documented justification, which links the quantitative benchmark to the qualitative realities of the market, is the core of a defensible best execution process.

![A robust, dark metallic platform, indicative of an institutional-grade execution management system. Its precise, machined components suggest high-fidelity execution for digital asset derivatives via RFQ protocols](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-platform-high-fidelity-price-discovery-and-atomic-settlement-infrastructure.jpg)

## The Operational Protocol for Price Validation

The transition from strategy to execution requires the formalization of a precise, auditable protocol. When faced with an order for an illiquid instrument, the execution desk cannot simply rely on a single model output. A robust operational workflow must be initiated to build a body of evidence supporting the eventual execution price. This protocol is the firm’s primary defense in any subsequent review of its best execution diligence.

The process begins with the generation of the initial benchmark price from the firm’s approved valuation model. This price, along with its key inputs and assumptions, forms the initial entry in the trade file. However, this is merely the starting point. The protocol then mandates a series of corroborating actions designed to test the reasonableness of this initial benchmark.

- 
**Internal Sanity Check** ▴ The first step is a comparison of the model-derived price against any recent, internal trades of the same or a very similar security. This check is designed to ensure consistency and identify any immediate discrepancies between the model’s output and the firm’s own recent experience.

- 
**External Data Inquiry** ▴ The protocol should require the trader or a supporting team to gather any available, albeit non-binding, external data points. This could include:

<li>**Broker-dealer indications** ▴ Reaching out to two or three market-making desks for indicative levels. While not firm quotes, these indications provide a valuable snapshot of where market participants perceive value.

- **Recent trade prints** ▴ Reviewing trade reporting facilities (like FINRA’s TRACE for fixed income) for any recent trades in the security or in a basket of highly comparable securities.

- **Pricing service data** ▴ Comparing the internal model price to the evaluation provided by a third-party pricing service, if available. Discrepancies must be investigated and explained.

</li>
- 
**Documentation of Factors** ▴ The execution protocol must include a formal checklist of the qualitative factors that must be considered and documented for every trade. This transforms the abstract requirements of best execution into a concrete set of operational tasks. This documentation is the narrative that explains why the final execution price was the most favorable possible under the specific circumstances of the trade.

![Polished metallic pipes intersect via robust fasteners, set against a dark background. This symbolizes intricate Market Microstructure, RFQ Protocols, and Multi-Leg Spread execution](https://options.greeks.live/wp-content/uploads/2025/07/precision-engineered-metallic-nodes-illustrating-rfq-protocols-for-multi-leg-digital-asset-derivatives-institutional-execution.jpg)

## Quantitative Inputs and Sensitivity Analysis

The credibility of the model-derived price is a direct function of the quality of its inputs. The execution protocol must specify the approved sources for these inputs and require a sensitivity analysis to understand how changes in key assumptions affect the final valuation. This demonstrates a deep understanding of the model’s mechanics and its potential for variability.

| Input Parameter | Primary Source | Secondary Source / Cross-Check | Impact on Valuation | Required Documentation |
| --- | --- | --- | --- | --- |
| Base Yield Curve | On-the-run Treasury curve | Swap curve | High | Snapshot of the curve at the time of valuation. |
| Credit Spread | CDS market for the issuer or sector | Spreads from comparable bonds (matrix pricing) | High | List of comparable bonds used and their spreads. |
| Assumed Default Rate | Agency ratings (Moody’s, S&P) | Internal credit research | Medium | Justification for any deviation from agency-implied rates. |
| Liquidity Premium | Historical bid-ask spreads | Third-party academic studies | Medium-High | Rationale for the chosen premium percentage. |
| Volatility | Implied volatility from options market | Historical volatility of the asset or proxy | High (for option-based models) | Source of volatility data and time period used. |

![A central glowing core within metallic structures symbolizes an Institutional Grade RFQ engine. This Intelligence Layer enables optimal Price Discovery and High-Fidelity Execution for Digital Asset Derivatives, streamlining Block Trade and Multi-Leg Spread Atomic Settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-engine-microstructure-core.jpg)

## A Case Study in Procedural Diligence

Consider a portfolio manager needing to sell a $10 million block of a seven-year, unrated corporate bond from a private company. The market for this bond is highly illiquid, with no active quotes. The firm’s execution protocol is immediately triggered.

The trading desk first runs the bond through its proprietary DCF model, which uses the 7-year swap curve as a base, adds a credit spread derived from a basket of publicly traded single-B rated industrial bonds, and incorporates a 75 basis point liquidity premium based on the firm’s internal guidelines for unrated paper. The model generates a benchmark price of $92.50.

This price is not the final answer. The trader then contacts three independent bond desks. Desk A provides an indicative bid of “around 91,” Desk B indicates “low 90s,” and Desk C declines to provide a level, citing no immediate interest. These indications are logged in the trade file.

Simultaneously, a review of TRACE data reveals no trades in this specific bond for the past six months, but a smaller trade in a bond from the same issuer with a shorter maturity occurred three weeks ago at a price equivalent to a 50 basis point wider spread. This data point is also added to the file. The portfolio manager has indicated a desire for a swift execution to free up capital for a new opportunity, adding a time-sensitivity factor. Armed with this complete picture ▴ a model price of $92.50, market color in the low 90s, historical data suggesting a wider spread, and a client need for speed ▴ the trader engages with Desk B. After a brief negotiation, they execute the full block at $91.75. The final trade ticket is accompanied by a detailed execution memorandum that outlines the entire process ▴ the initial model price, the external indications, the relevant market data, the client’s instructions, and the final rationale for determining that $91.75 represented the best possible outcome under these specific “facts and circumstances.” This comprehensive documentation is what transforms the model-derived price from a mere estimate into a sufficient and defensible benchmark for best execution.

![Multi-faceted, reflective geometric form against dark void, symbolizing complex market microstructure of institutional digital asset derivatives. Sharp angles depict high-fidelity execution, price discovery via RFQ protocols, enabling liquidity aggregation for block trades, optimizing capital efficiency through a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-protocol-liquidity-aggregation-engine.jpg)

![A polished metallic disc represents an institutional liquidity pool for digital asset derivatives. A central spike enables high-fidelity execution via algorithmic trading of multi-leg spreads](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-liquidity-system.jpg)

## References

- FINRA. (2015). Regulatory Notice 15-46 ▴ Guidance on Best Execution Obligations in Equity, Options and Fixed Income Markets. Financial Industry Regulatory Authority.

- Securities and Exchange Commission. (2020). Final Rule ▴ Good Faith Determinations of Fair Value. Release No. IC-34128.

- O’Hara, M. (1995). Market Microstructure Theory. Blackwell Publishers.

- Harris, L. (2003). Trading and Exchanges ▴ Market Microstructure for Practitioners. Oxford University Press.

- Cont, R. & Tankov, P. (2004). Financial Modelling with Jump Processes. Chapman and Hall/CRC.

- Duffie, D. & Singleton, K. J. (1999). Modeling Term Structures of Defaultable Bonds. The Review of Financial Studies, 12(4), 687-720.

- Amihud, Y. (2002). Illiquidity and stock returns ▴ cross-section and time-series effects. Journal of Financial Markets, 5(1), 31-56.

- Freyre-Sanders, A. Guobuzaite, R. & Byrne, K. (2004). Market Impact Models, Analysis and Trading. Tabb Group.

- Angel, J. J. Harris, L. E. & Spatt, C. S. (2011). Equity Trading in the 21st Century ▴ An Update. The Wharton School, University of Pennsylvania.

- European Securities and Markets Authority. (2015). Technical Advice to the Commission on MiFID II and MiFIR. ESMA/2015/1861.

![A sleek, multi-layered digital asset derivatives platform highlights a teal sphere, symbolizing a core liquidity pool or atomic settlement node. The perforated white interface represents an RFQ protocol's aggregated inquiry points for multi-leg spread execution, reflecting precise market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-core-execution-system.jpg)

## Reflection

![Two sleek, abstract forms, one dark, one light, are precisely stacked, symbolizing a multi-layered institutional trading system. This embodies sophisticated RFQ protocols, high-fidelity execution, and optimal liquidity aggregation for digital asset derivatives, ensuring robust market microstructure and capital efficiency within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-grade-digital-asset-derivatives-platform-architecture-high-fidelity-execution-protocols-and-liquidity-aggregation.jpg)

## The Synthesis of System and Judgment

The successful use of a model-derived price as a best execution benchmark is ultimately a reflection of a firm’s operational philosophy. It demonstrates a synthesis of quantitative systems and qualitative human judgment. The model provides the objective, repeatable anchor, a necessary shield against claims of arbitrary decision-making. Yet, it is the documented, reason-based deviations from this anchor ▴ driven by the unquantifiable realities of market impact, client needs, and latent liquidity ▴ that demonstrate true diligence.

Considering this framework, the essential question for any institution is not whether its models are accurate in an absolute sense, an impossible standard for illiquid assets. The more salient inquiry is whether the firm’s operational architecture treats the model’s output as the beginning of a rigorous diligence process or as its conclusion. A price, however expertly calculated, is static.

A market, however illiquid, is dynamic. A truly superior execution framework is one that provides its professionals with the tools to navigate the space between the two, and the structure to defend their path.

![A dark, precision-engineered module with raised circular elements integrates with a smooth beige housing. It signifies high-fidelity execution for institutional RFQ protocols, ensuring robust price discovery and capital efficiency in digital asset derivatives market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-system-core-high-speed-price-discovery-module.jpg)

## Glossary

<a href="https://prime.greeks.live/area/model-derived-price/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A robust, multi-layered institutional Prime RFQ, depicted by the sphere, extends a precise platform for private quotation of digital asset derivatives. A reflective sphere symbolizes high-fidelity execution of a block trade, driven by algorithmic trading for optimal liquidity aggregation within market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/robust-institutional-platform-for-digital-asset-derivatives-rfq-protocols-and-optimized-liquidity-aggregation.jpg)

## Model-Derived Price

Meaning ▴ A Model-Derived Price, in the context of crypto investing and institutional options trading, is a theoretical valuation for a digital asset or derivative contract generated through a quantitative computational model, rather than directly observed from an active market order book. </a><a href="https://prime.greeks.live/area/best-execution/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![An advanced RFQ protocol engine core, showcasing robust Prime Brokerage infrastructure. Intricate polished components facilitate high-fidelity execution and price discovery for institutional grade digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-engine-core-for-precision-trading.jpg)

## Best Execution

Meaning ▴ Best Execution, in the context of cryptocurrency trading, signifies the obligation for a trading firm or platform to take all reasonable steps to obtain the most favorable terms for its clients' orders, considering a holistic range of factors beyond merely the quoted price. </a><a href="https://prime.greeks.live/area/mark-to-model/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstract geometric structure with sharp angles and translucent planes, symbolizing institutional digital asset derivatives market microstructure. The central point signifies a core RFQ protocol engine, enabling precise price discovery and liquidity aggregation for multi-leg options strategies, crucial for high-fidelity execution and capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/principals-operational-framework-optimizing-institutional-digital-asset-derivatives-rfq-protocol-execution-for-alpha-generation.jpg)

## Mark-To-Model

Meaning ▴ Mark-to-Model is a valuation methodology where the fair value of an asset or liability is determined using financial models, rather than observable market prices, typically because an active market for that specific instrument does not exist or is illiquid. </a><a href="https://prime.greeks.live/area/fair-value/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A central metallic bar, representing an RFQ block trade, pivots through translucent geometric planes symbolizing dynamic liquidity pools and multi-leg spread strategies. This illustrates a Principal's operational framework for high-fidelity execution and atomic settlement within a sophisticated Crypto Derivatives OS, optimizing private quotation workflows](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-facilitating-high-fidelity-price-discovery-and-optimal-capital-efficiency-within-advanced-market-microstructure.jpg)

## Fair Value

Meaning ▴ Fair value, in financial contexts, denotes the theoretical price at which an asset or liability would be exchanged between knowledgeable, willing parties in an arm's-length transaction, where neither party is under duress. </a><a href="https://prime.greeks.live/area/asc-820/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Close-up of intricate mechanical components symbolizing a robust Prime RFQ for institutional digital asset derivatives. These precision parts reflect market microstructure and high-fidelity execution within an RFQ protocol framework, ensuring capital efficiency and optimal price discovery for Bitcoin options](https://options.greeks.live/wp-content/uploads/2025/07/engineered-core-systems-driving-institutional-digital-asset-derivatives-rfq-protocol-execution.jpg)

## Asc 820

Meaning ▴ ASC 820, or Accounting Standards Codification 820, establishes the authoritative guidance for measuring fair value within US Generally Accepted Accounting Principles (GAAP). </a>

**Tags:** [Best Execution](https://options.greeks.live/area/best-execution/), [Price Discovery](https://options.greeks.live/area/price-discovery/), [Model-Derived Price](https://options.greeks.live/area/model-derived-price/), [FINRA Rule 5310](https://options.greeks.live/area/finra-rule-5310/), [Operational Diligence](https://options.greeks.live/area/operational-diligence/), [Market Microstructure](https://options.greeks.live/area/market-microstructure/)	

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Best execution in RFQs shifts from quantitative price optimization for liquid assets to qualitative, diligent price discovery for illiquid ones.

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Quantifying best execution for illiquids is a process of validating the integrity of price discovery, not measuring against an absent benchmark.

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Best execution shifts from optimizing price in liquid markets to discovering price and access in illiquid ones.

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### [What Are the Key Differences in Documenting Best Execution for Equities versus Otc Derivatives?](https://options.greeks.live/question/what-are-the-key-differences-in-documenting-best-execution-for-equities-versus-otc-derivatives/)
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Documenting best execution contrasts proving a quantitative outcome in transparent equity markets with demonstrating a robust process in opaque OTC derivative markets.

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Firms evidence best execution for illiquid bonds by systemically constructing an auditable, data-rich narrative through a structured RFQ process.

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The primary challenge is constructing a valid benchmark in an environment defined by data scarcity and private, ephemeral quotes.

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Measuring execution quality differs in that CLOB analysis assesses performance against a visible, continuous public benchmark, while RFQ analysis reconstructs a hypothetical competitive benchmark to validate a private negotiation.

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---

**Original URL:** https://options.greeks.live/question/can-a-model-derived-price-serve-as-a-sufficient-benchmark-for-best-execution-in-the-absence-of-quotes/
