What Are the Key Data Points Required to Prove Best Execution under MiFID II? ▴ Question

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Concept

The mandate to demonstrate best execution under the Markets in Financial Instruments Directive (MiFID II) has undergone a significant operational recalibration. The recent discontinuation of the formal reporting obligations under Regulatory Technical Standards (RTS) 27 and 28 signals a pivotal shift in regulatory focus. This evolution moves the entire framework away from a periodic, compliance-driven reporting exercise toward a continuous, evidence-based operational discipline. The core obligation for an investment firm to take “all sufficient steps” to obtain the best possible result for its clients has been reinforced, placing the internal data architecture and analytical capabilities of the firm at the center of the supervisory model.

Proving best execution is now an expression of a firm’s systemic integrity. It requires the capacity to construct and present a defensible narrative of every execution, substantiated by a granular and coherent set of data points. This is not a matter of simply archiving trade blotters.

It is the methodical assembly of a decision-making audit trail, where each data element serves as a load-bearing component in the structure of proof. The objective is to demonstrate, with quantitative rigor, that the firm’s Order Execution Policy (OEP) is not a static document but a living system that actively optimizes for a client-centric outcome across a spectrum of execution factors.

The key data points, therefore, are the fundamental inputs into this system. They are the atomic units of information that, when aggregated and analyzed, provide a complete chronology and context for every order. This encompasses the full lifecycle of a trade, from the moment of the client’s instruction to the final settlement.

The quality and completeness of this data set directly determine a firm’s ability to validate its execution strategy, justify its choice of venues, and ultimately, withstand regulatory scrutiny. The framework demands a forensic level of detail, transforming the act of execution from a simple transaction into a quantifiable and defensible process.

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Strategy

With the dissolution of prescriptive reporting templates, the strategic nucleus of MiFID II best execution now resides entirely within the firm’s Order Execution Policy (OEP). This document is elevated from a disclosure requirement to the central strategic blueprint governing all execution activities. A robust OEP functions as the firm’s constitution for routing and handling client orders, articulating the precise methodology used to balance the competing dynamics of the core execution factors.

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The Hierarchy of Execution Factors

The directive compels firms to weigh a series of factors to achieve the optimal outcome for a client. The strategic challenge lies in creating a flexible, yet consistent, framework for prioritizing these factors based on client classification, order characteristics, and prevailing market conditions. The OEP must explicitly define this logic.

Price ▴ The primary consideration for most execution scenarios, representing the dealing price of the financial instrument.
Costs ▴ All expenses incurred by the client that are directly related to the execution of the order. This includes execution venue fees, clearing and settlement fees, and any other commissions paid to third parties involved in the execution.
Speed of Execution ▴ The elapsed time between the receipt of an order and its final execution. The strategic importance of this factor varies dramatically between different trading strategies.
Likelihood of Execution and Settlement ▴ A qualitative and quantitative assessment of a venue’s or counterparty’s ability to complete the trade as intended and ensure a smooth settlement process. This is particularly relevant for illiquid instruments or large order sizes.
Size and Nature of the Order ▴ The characteristics of the order itself, which can influence the choice of execution method (e.g. algorithmic, RFQ, direct market access) and venue (e.g. lit market, dark pool, systematic internaliser) to minimize market impact.

A firm’s execution strategy is codified in its Order Execution Policy, which must detail the systematic process for weighing factors like price, cost, and speed for different financial instruments and client types.

The strategic implementation of the OEP requires a dynamic data feedback loop. The data collected from every trade must be systematically analyzed to monitor the effectiveness of the policy and the quality of execution delivered by the selected venues. This creates a cycle of continuous improvement where the execution strategy is refined based on empirical evidence, ensuring it adapts to changes in market structure and venue performance.

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Venue Analysis as a Core Strategic Pillar

Even without the mandate to publish a top-five venue report (the former RTS 28), the underlying analytical process remains a critical strategic activity. A firm must be able to provide a data-driven justification for its selection of execution venues for each class of financial instrument. This involves a periodic and rigorous assessment of the execution quality available from all potential venues.

The following table outlines the strategic data analysis required for this internal venue selection and review process, forming a core component of the evidence required to substantiate the OEP.

Table 1 ▴ Strategic Venue Analysis Framework
Analysis Dimension	Key Data Points Required	Strategic Objective	Applicable Instrument Classes
Cost Analysis	Explicit fee schedules, clearing and settlement charges, implicit costs (e.g. spread, market impact).	To quantify the total cost of execution for each venue and identify the most cost-effective routing options for specific order types.	Equities, Fixed Income, Derivatives
Price Improvement Analysis	Executed price vs. European Best Bid and Offer (EBBO) at time of execution, frequency and magnitude of price improvement.	To measure the value added by venues that offer execution at prices superior to the prevailing market quote.	Equities, ETFs
Execution Speed & Certainty	Timestamp data (order receipt, routing, execution), order fill rates, cancellation rates.	To evaluate a venue’s latency profile and its reliability in executing orders, which is critical for latency-sensitive strategies.	All classes, especially for algorithmic trading
Liquidity Profile	Average daily volume, average trade size, available liquidity at various price levels, Large-in-Scale (LIS) thresholds.	To match large or illiquid orders with venues that possess sufficient depth to minimize market impact and information leakage.	All classes, especially for block trades

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Execution

The operational execution of a MiFID II-compliant best execution framework is a data-intensive undertaking. It requires a sophisticated technological infrastructure capable of capturing, storing, and analyzing a vast array of data points in near real-time. The focus is on creating an immutable, auditable record for every single client order, which serves as the foundational evidence for all subsequent analysis and reporting, whether for internal review or regulatory request.

The Foundational Data Layer

At the most granular level, the firm must capture a complete set of intra-trade data points. This data forms the raw material for all Transaction Cost Analysis (TCA) and execution quality monitoring. The absence of any of these elements creates a critical gap in the audit trail, undermining the ability to prove that “all sufficient steps” were taken.

The table below details the essential data fields that must be captured at the individual order level. This represents the minimum viable data set for a compliant execution monitoring system.

Table 2 ▴ Core Intra-Order Data Elements
Data Point	Description	Granularity Requirement	Systemic Purpose
Unique Order Identifier	A unique ID assigned to the client order upon receipt.	Alphanumeric String	Links all related child orders and executions back to the original client instruction.
Instrument Identifier	The ISIN code for the financial instrument being traded.	ISO 6166	Ensures unambiguous identification of the security for accurate market data comparison.
Client Information	An identifier for the client and their classification (Retail or Professional).	Internal ID & Flag	Determines the applicable level of protection and the relative importance of execution factors.
Order Timestamps	Timestamps for key events ▴ order receipt, order transmission, execution(s), and cancellation.	Microsecond (or finest available)	Critical for calculating latency and for benchmarking against market conditions at precise moments in time.
Order Details	Quantity, price (for limit orders), order type (market, limit, etc.), and validity period.	Numeric & Categorical	Defines the client’s instructions and the constraints within which the firm must operate.
Execution Venue ID	The Market Identifier Code (MIC) of the venue where the trade was executed.	ISO 10383	Attributes execution quality metrics to specific venues for ongoing performance analysis.
Execution Price	The price at which each fill of the order was executed.	Decimal to instrument’s tick size	The primary input for calculating execution performance against benchmarks.
Executed Quantity	The quantity of the instrument executed in each fill.	Integer	Tracks the progress of the order towards completion.
Direct Costs	All explicit costs charged to the client, including venue fees and broker commissions.	Currency Value	Required to calculate the total consideration and net execution quality.

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The Analytical Process for Demonstrating Compliance

Once the foundational data is captured, it must be processed through a rigorous analytical framework. This is where the firm moves from data collection to evidence generation. The process involves comparing the firm’s execution results against a variety of independent benchmarks to produce quantitative metrics of execution quality.

Demonstrating best execution requires a systematic, data-driven process that transforms raw trade data into quantifiable metrics of performance against established market benchmarks.

This analytical process forms the core of the firm’s Best Execution Committee or equivalent governance function. It is a continuous, cyclical process, not a one-time event.

Data Ingestion and Normalization ▴ The first step involves aggregating the core data elements from various sources (Order Management Systems, Execution Management Systems, venue reports) into a centralized data warehouse. Data is cleaned and normalized to ensure consistency, for instance, by synchronizing all timestamps to a single standard (e.g. UTC).
Benchmark Data Acquisition ▴ The system must ingest high-quality market data for the relevant period. This includes tick-by-tick quote data from all relevant venues to reconstruct the state of the market (e.g. the EBBO) at the exact time of execution. It also includes data for calculating standard benchmarks like Volume-Weighted Average Price (VWAP) or Time-Weighted Average Price (TWAP).
Transaction Cost Analysis (TCA) ▴ This is the quantitative core of the process. The captured execution data is compared against the benchmark data to calculate performance metrics. A primary metric is Implementation Shortfall, which measures the total cost of execution relative to the market price at the moment the decision to trade was made (the arrival price).
Internal Reporting and Review ▴ The TCA results are compiled into execution quality reports. These reports are reviewed by the firm’s Best Execution Committee. The review process must be systematic, analyzing performance by asset class, venue, client type, and execution algorithm. Any outliers or instances of poor performance must be investigated and documented.
Policy and Venue Adjustment ▴ The final step is the feedback loop. The insights gained from the analysis are used to refine the Order Execution Policy. This could involve changing the default routing logic for certain order types, adding or removing venues from the approved list, or adjusting the parameters of execution algorithms. This demonstrates that the firm is using data to actively manage and improve its execution outcomes.

This entire workflow provides the comprehensive body of evidence a firm needs to demonstrate its adherence to the best execution obligation. It shows not only what happened with a given order, but also that a systematic, data-driven process is in place to monitor and optimize performance for the benefit of its clients.

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References

European Securities and Markets Authority. (2024, February 13). ESMA clarifies certain best execution reporting requirements under MiFID II. ESMA.
European Securities and Markets Authority. (2022, December 14). ESMA clarifies position on RTS 27 reports. ESMA.
International Capital Market Association. (2016, September). MiFID II/R Fixed Income Best Execution Requirements RTS 27 & 28.
European Parliament and Council. (2014). Directive 2014/65/EU on markets in financial instruments (MiFID II). Official Journal of the European Union.
Commission Delegated Regulation (EU) 2017/575 of 8 June 2016 supplementing Directive 2014/65/EU of the European Parliament and of the Council on markets in financial instruments with regard to regulatory technical standards for the data to be published by execution venues on the quality of execution of transactions.
Commission Delegated Regulation (EU) 2017/576 of 8 June 2016 supplementing Directive 2014/65/EU of the European Parliament and of the Council with regard to regulatory technical standards for the annual publication by investment firms of information on the identity of execution venues and on the quality of execution.
Hill, Andy. (2018). Demystifying MiFID II. BNY Mellon.
Lehalle, Charles-Albert, and Sophie Laruelle, eds. (2013). Market Microstructure in Practice. World Scientific Publishing.
Harris, Larry. (2003). Trading and Exchanges ▴ Market Microstructure for Practitioners. Oxford University Press.
O’Hara, Maureen. (1995). Market Microstructure Theory. Blackwell Publishers.

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Reflection

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From Obligation to Asset

The evolution of the MiFID II best execution framework presents a fundamental challenge to an investment firm’s operational perspective. The necessary data infrastructure, once viewed as a system for fulfilling a regulatory reporting burden, must now be recognized as a core strategic asset. The ability to capture, analyze, and act upon a granular stream of execution data is the primary determinant of a firm’s capacity to navigate modern market structures effectively. The quality of this internal data ecosystem directly translates into the quality of the execution delivered to clients.

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A System of Continuous Intelligence

Viewing the best execution process through an architectural lens reveals a system of continuous intelligence. Each trade executed is a query to the market, and the resulting data is the market’s response. A sophisticated data framework allows a firm to interpret these responses, identify patterns of venue performance, and understand the subtle costs of execution.

This creates a powerful feedback loop where strategic decisions within the Order Execution Policy are informed by a constant flow of empirical evidence. The ultimate objective is a state of operational command, where the firm possesses a quantifiable and defensible understanding of its own execution performance, enabling it to deliver a superior outcome for its clients with precision and consistency.