What Are the Primary Challenges in Applying MiFID II Best Execution Standards to Illiquid Assets?

Concept

The core challenge in applying MiFID II’s best execution standards to illiquid assets is a fundamental collision between a regulatory framework architected for data-rich environments and a market reality defined by data scarcity. The directive, in its elevation from “all reasonable steps” to “all sufficient steps,” presupposes the existence of a continuous, observable, and comparable data stream against which execution quality can be measured. For liquid equities or actively traded futures, this premise holds.

A firm can systematically ingest market data from multiple lit venues, apply a Transaction Cost Analysis (TCA) model, and produce a defensible, quantitative report card on its performance against benchmarks like VWAP or implementation shortfall. This entire system is predicated on the constant availability of price, volume, and liquidity data.

Illiquid assets, such as bespoke over-the-counter (OTC) derivatives, non-public equity, or thinly traded corporate bonds, operate in a diametrically opposed reality. Their defining characteristic is the absence of a centralized, continuous price formation process. Liquidity is fragmented, episodic, and often sourced through bilateral, voice-based negotiations or Request for Quote (RFQ) protocols.

Consequently, the quantitative evidence chain that underpins best execution in liquid markets is broken from the start. There is no persistent public tape to analyze, no comparable set of simultaneous trades to benchmark against, and often, no readily available pre-trade price against which to measure performance.

The central problem is not one of unwillingness to comply, but of architectural incompatibility between the regulation’s data demands and the market’s structure.

The Data Void in Illiquid Markets

The primary challenge is the “data void.” MiFID II requires firms to consider a hierarchy of execution factors ▴ price, costs, speed, and the likelihood of execution and settlement. In a liquid market, these factors are quantifiable. For an illiquid instrument, each factor presents a unique data collection problem.

• Price ▴ Without a continuous order book, the “price” is not a single, observable data point. It is a negotiated outcome derived from a limited set of counterparties at a specific moment. The concept of a “fair price” becomes a matter of judgment and process, not a simple comparison to a market feed.
• Costs ▴ While explicit costs like commissions are clear, the implicit costs, such as the market impact of signaling trading intent in a shallow market, are immense and nearly impossible to quantify with the same precision as in liquid markets.
• Speed ▴ The speed of execution is often secondary to the need to find any counterparty at all. A protracted search for liquidity might yield a far better result than a quick, uninformed trade.
• Likelihood of Execution ▴ For many illiquid assets, this is the paramount factor. The primary risk is often execution failure, which has no equivalent in the liquid world where market orders are virtually guaranteed to be filled. Proving that a firm optimized for likelihood of execution requires documenting the search process itself.

Therefore, the challenge shifts from a quantitative post-trade analysis to a qualitative, process-oriented demonstration of diligence. The system of proof must be re-architected away from analyzing the outcome (the price) and towards evidencing the integrity of the process used to arrive at that outcome. This requires a profound shift in mindset, technology, and operational procedure for any trading desk.

What Constitutes a Sufficient Search for Liquidity?

How can a firm prove it took “all sufficient steps” when the universe of potential outcomes is unknowable? This question reveals the core tension. For illiquid assets, the regulator’s focus invariably shifts to the firm’s execution policy and the auditable evidence of its application. The firm must construct and document a systematic, repeatable process for sourcing liquidity and validating prices, even in the absence of public data.

This moves the burden of proof from a simple data report to a comprehensive narrative of the trade’s lifecycle, supported by meticulous record-keeping. The challenge is building an operational architecture that can capture this narrative in a way that satisfies regulatory scrutiny.

Strategy

Confronted with the architectural mismatch between MiFID II’s data-centric design and the reality of illiquid markets, a successful strategy requires a fundamental pivot. The focus must shift from proving the quality of an execution outcome via quantitative benchmarks to demonstrating the robustness of the execution process itself. The strategic objective is to build a defensible, auditable system that evidences a consistent and diligent search for the best possible result for the client, even when that result cannot be validated against a public tape.

Architecting a Process-Driven Defense

The cornerstone of this strategy is the development of a highly structured and documented execution policy tailored specifically to different classes of illiquid instruments. This policy becomes the firm’s primary piece of evidence. It must clearly articulate the methodologies used to source liquidity, establish fair value, and select execution venues or counterparties. This is a move from a reactive, post-trade analytical framework to a proactive, pre-trade procedural one.

The strategy involves several key pillars:

1. Systematic Liquidity Sourcing ▴ The ad-hoc nature of sourcing liquidity for illiquid assets must be replaced with a systematic protocol. This means defining, for each asset class, the number and type of counterparties to approach via a bilateral price discovery process. For instance, a policy for an illiquid corporate bond might mandate soliciting quotes from a minimum of three to five market makers known to be active in that sector. The entire process, including non-responsive or non-competitive quotes, must be logged.
2. Proxy-Based Fair Value Assessment ▴ In the absence of a direct market price, firms must construct a “fair value” benchmark pre-trade. This involves using data from correlated, more liquid instruments. For a corporate bond, this could involve using a government bond yield of a similar duration, adding the credit spread from a relevant credit default swap (CDS) index or a more liquid bond from the same issuer, and then applying an estimated liquidity premium. This calculated fair value serves as the internal benchmark against which received quotes are judged.
3. Dynamic Factor Weighting ▴ The MiFID II execution factors (price, cost, speed, likelihood) must be weighted differently for illiquid assets. A firm’s policy must explicitly state that for certain instruments, likelihood of execution and settlement takes precedence over price and speed. This pre-defined policy provides the justification for executing a trade at a price that may appear suboptimal in isolation but was the best achievable result given the paramount need to complete the order.

From Quantitative TCA to Qualitative Process Analysis

The traditional model of Transaction Cost Analysis (TCA) is insufficient for illiquid assets. The strategy is to augment or replace it with a system of Qualitative Process Analysis (QPA). This system does not measure slippage against a non-existent benchmark; it audits adherence to the pre-defined execution policy. It answers questions like ▴ Did the trader follow the documented liquidity sourcing protocol?

Was the fair value assessment conducted and recorded pre-trade? Was the rationale for selecting a specific counterparty documented? This creates a robust audit trail that serves as the evidence of diligence.

A well-defined process, consistently followed and meticulously documented, becomes the most compelling evidence of best execution in an illiquid environment.

The table below contrasts the evidentiary frameworks for liquid and illiquid assets, illustrating the strategic shift required.

This strategic reorientation requires significant investment in the firm’s operational architecture. Execution Management Systems (EMS) must be configured to capture not just trades, but the entire lifecycle of a quote solicitation. This includes logging timestamps, counterparty names, quotes received (both verbal and electronic), and the trader’s rationale for decision-making. The system must be designed for evidence capture as a primary function.

Execution

The execution of a best execution policy for illiquid assets is an exercise in operational discipline and technological integration. It translates the strategic framework into a series of concrete, auditable actions performed by traders and supported by the firm’s systems. The ultimate goal is to create an evidentiary package for every illiquid trade that is so thorough it reconstructs the market environment at the time of execution and demonstrates that the firm’s actions were sufficient and defensible.

The Operational Playbook a Step by Step Guide

Executing an order for an illiquid instrument, such as a 5 million EUR block of a non-benchmark corporate bond, requires a fundamentally different workflow than executing a liquid equity trade. The process must be formalized into a playbook that ensures consistency and captures the necessary data for the audit trail.

• Step 1 Pre-Trade Intelligence Gathering ▴ Before any quotes are solicited, the trader must assemble a pre-trade “intelligence file.” This involves using market data terminals and internal knowledge bases to identify dealers known to have an axe in the specific bond or sector. The trader documents this initial list of potential counterparties.
• Step 2 Fair Value Calculation ▴ The trader, or a dedicated pricing desk, constructs a pre-trade fair value estimate. This calculation, as detailed in the table below, is timestamped and saved. This is the central reference point for the entire execution process. It is the internal, evidence-based opinion of what the bond is worth before the market is ever touched.
• Step 3 Systematic Quote Solicitation (RFQ) ▴ The trader initiates the RFQ process, contacting the identified dealers. The playbook dictates that dealers should be contacted in a structured manner. Critically, every interaction is logged in the EMS. This includes the time of the call or message, the dealer’s response (or lack thereof), the price and size quoted, and any qualitative “market color” provided. A “no bid” is as important a piece of evidence as a firm quote.
• Step 4 Quote Evaluation and Execution ▴ The trader evaluates the received quotes against the pre-trade fair value calculation. The decision to trade is based not just on the best price, but on a combination of price, quoted size (to avoid partial fills), and perceived settlement risk of the counterparty. The trader must document the final execution rationale in the EMS, explicitly referencing the execution factors that drove the decision. For example ▴ “Executed with Dealer B at 98.75. Although Dealer A quoted 98.80, their quote was for 1M only. Dealer B’s quote was for the full 5M size, satisfying the likelihood of execution factor which is paramount for this order.”
• Step 5 Post-Trade Documentation Assembly ▴ Immediately following the trade, the system automatically assembles the best execution file. This file contains the pre-trade intelligence file, the timestamped fair value calculation, the complete log of all quote solicitations (including failures), the final execution details, and the trader’s documented rationale. This file serves as the definitive proof of the “all sufficient steps” taken.

Quantitative Modeling Fair Value in a Vacuum

The credibility of the entire execution process for illiquid assets hinges on the robustness of the pre-trade fair value calculation. This model provides the objective anchor in a subjective market. The following table provides a granular example of how such a model might be constructed for an illiquid corporate bond.

How Should Technology Support This Process?

The execution playbook cannot function without the proper technological architecture. The firm’s Execution Management System must be more than a simple order routing machine; it must be an evidence-gathering system. The key requirement is the ability to integrate structured data (like electronic quotes) with unstructured data (like trader notes from a phone call) into a single, time-sequenced record for each order.

The EMS must have dedicated fields for logging the rationale behind decisions and must be able to produce the final best execution file on demand for compliance and audit teams. This integration is the final, critical link in translating regulatory theory into defensible operational practice.

Reflection

The framework for applying best execution to illiquid assets forces a deeper consideration of what “diligence” truly means. It moves the conversation from the comfort of algorithmic certainty to the more demanding realm of professional judgment, supported by a rigorous operational architecture. The systems and protocols a firm builds to meet this challenge do more than satisfy a regulator. They create a permanent, evidence-based record of the firm’s market intelligence and decision-making process.

Consider your own operational framework. Is it designed merely to execute trades, or is it architected to capture intelligence? Does it treat the data from a failed quote solicitation as noise to be discarded, or as a valuable signal about market depth and appetite?

The process of building a MiFID II-compliant system for illiquid assets is an opportunity to construct a more intelligent, self-aware trading apparatus. The end result is a system that not only defends past actions but also informs future ones, turning a compliance mandate into a source of durable competitive advantage.