What Are the Key Components of a MiFID II Best Execution Report?

Concept

The Markets in Financial Instruments Directive II (MiFID II) framework introduced a stringent set of requirements aimed at enhancing investor protection and promoting market integrity. Central to this regulatory landscape are the obligations surrounding best execution, which compel investment firms to take all sufficient steps to achieve the most favorable outcome for their clients when executing orders. This principle is operationalized through detailed reporting mechanisms, primarily the Regulatory Technical Standards (RTS) 27 and RTS 28 reports. These documents serve as the evidentiary backbone of a firm’s commitment to its clients, transforming the abstract concept of “best execution” into a series of quantifiable and comparable metrics.

The RTS 27 report is a quarterly disclosure made by execution venues, such as stock exchanges, multilateral trading facilities (MTFs), and systematic internalisers (SIs). Its purpose is to provide a standardized set of data on execution quality, allowing market participants to compare performance across different venues. This report is granular, breaking down information by financial instrument and covering a wide array of metrics that illuminate the quality of execution available on that platform. While investment firms themselves do not produce RTS 27 reports, the data contained within them is a critical input for their own internal processes and for fulfilling their obligations under RTS 28.

Conversely, the RTS 28 report is an annual publication by investment firms that execute client orders. This report provides a summary of the top five execution venues used for each class of financial instrument, based on trading volume, and a qualitative assessment of the execution quality achieved. It is a public-facing document designed to offer clients and the public insight into a firm’s order routing practices and the effectiveness of its execution policy. The report must detail how the firm has monitored execution quality and the rationale behind its choice of venues, linking its practices directly to the overarching goal of securing the best possible results for its clients.

A MiFID II best execution report is a mandated disclosure that provides transparent, quantitative, and qualitative evidence of how an investment firm achieves the best possible results for its clients when executing orders.

It is important to understand the symbiotic relationship between these two reports. The data provided by execution venues in RTS 27 reports gives investment firms the raw material to conduct thorough due diligence and to monitor the performance of the venues they use. This information then informs the firm’s execution policy and its selection of venues, the results of which are summarized and explained in the annual RTS 28 report.

Together, they create a feedback loop intended to foster competition among venues and to hold investment firms accountable for their execution practices, ultimately benefiting the end investor. While regulatory reviews have led to suspensions and proposed changes to these reporting requirements, particularly for RTS 27, their foundational components continue to shape the industry’s approach to execution quality monitoring.

Strategy

A robust strategy for MiFID II best execution reporting extends far beyond mere compliance. It involves integrating the reporting process into the firm’s core operational and strategic framework, using the generated insights to drive continuous improvement in execution quality. The starting point for any such strategy is the firm’s Order Execution Policy, a document that must be clearly articulated and disclosed to clients. This policy outlines the relative importance the firm assigns to various execution factors, which are the pillars upon which the entire best execution framework is built.

The Execution Factors a Strategic Hierarchy

MiFID II specifies a range of execution factors that firms must consider. The strategic element comes from how a firm prioritizes these factors depending on the client’s status (retail or professional), the nature of the order, and the characteristics of the financial instrument. The primary factors include:

• Price ▴ The price at which the transaction is executed. For most retail clients, this is often the most important factor.
• Costs ▴ All expenses related to the execution of the order, including venue fees, clearing and settlement fees, and any commissions paid to the firm.
• Speed of Execution ▴ The time it takes to complete an order after it has been received. This is particularly relevant in fast-moving markets.
• Likelihood of Execution and Settlement ▴ The probability that the order will be successfully executed and settled, a critical consideration for illiquid instruments or large orders.
• Size and Nature of the Order ▴ The specific characteristics of the order, which may influence the choice of execution venue or method to minimize market impact.

A firm’s strategy must define how it weighs these factors. For a large institutional order in an illiquid stock, likelihood of execution and minimizing market impact might outweigh the raw price. For a small retail order in a liquid blue-chip stock, price and low costs are paramount. This prioritization is not static; it must be dynamic and responsive to changing market conditions and client needs.

The strategic core of MiFID II reporting lies in transforming a regulatory requirement into a dynamic feedback system for optimizing execution pathways and demonstrating superior client outcomes.

From Data to Decision the Role of RTS 27 and RTS 28

The strategic application of the reports themselves involves a two-stage process. First, the firm must consume and analyze the RTS 27 data provided by various execution venues. This analysis allows the firm to quantitatively assess and compare venues based on the firm’s own execution policy priorities. For example, a firm prioritizing speed can compare the average execution times reported by different MTFs for a specific class of derivatives.

Comparative Analysis of Execution Venues Using RTS 27 Data

The second stage is the production of the RTS 28 report. This is not just a data dump. It is a strategic communication tool. The report must provide a clear narrative explaining why the firm chose its top five venues.

This involves linking the quantitative analysis of venue performance (informed by RTS 27 data) back to the qualitative goals outlined in the Order Execution Policy. For instance, the report might explain that Venue C was a top choice for certain orders because its superior price improvement and lower direct costs aligned with the firm’s primary duty to achieve the best total consideration for its clients, even with a slightly slower execution speed.

This process creates a virtuous cycle. The analysis required for the RTS 28 report forces the firm to regularly scrutinize its execution outcomes. This scrutiny may reveal that a particular venue is no longer providing optimal results, or that a new venue offers a better combination of factors. This leads to adjustments in the firm’s order routing logic and execution policy, which will then be reflected in the following year’s RTS 28 report, demonstrating a commitment to ongoing optimization and client interests.

Execution

The execution of MiFID II best execution reporting is a complex, data-intensive process that requires a sophisticated operational and technological infrastructure. It is a discipline that combines regulatory interpretation, data engineering, quantitative analysis, and system integration. Successfully navigating this process transforms a compliance burden into a source of competitive advantage through superior execution intelligence.

The Operational Playbook

A successful implementation of MiFID II reporting follows a structured, multi-stage playbook. This operational guide ensures that all necessary data is captured, processed, and reported in a manner that is both compliant and strategically valuable.

1. Data Sourcing and Aggregation ▴ The first step is to identify and establish data feeds for all relevant execution information. This involves capturing order and execution data from internal systems like the Order Management System (OMS) and Execution Management System (EMS). This data must be enriched with market data and reference data to classify instruments correctly. For the RTS 28 report, this includes:
   • Order Details ▴ Timestamps (order receipt, execution), instrument identifier (ISIN), order type, size, and client classification.
   • Execution Details ▴ Venue of execution, execution price, volume, and associated costs (fees, commissions).
   • Venue Analysis Data ▴ Ingesting RTS 27 reports from all potential and current execution venues to build a comparative database of execution quality metrics.
2. Data Normalization and Cleansing ▴ Raw data from multiple sources will inevitably have inconsistencies in format, timing, and identifiers. A critical step is to normalize this data into a consistent internal format. This involves synchronizing timestamps to a central clock, mapping various instrument codes to a single identifier (e.g. ISIN), and cleansing the data of errors or duplicates. This stage is foundational for ensuring the accuracy of the final reports.
3. Classification and Segmentation ▴ The regulation requires reporting to be segmented by class of financial instrument. The firm must implement a robust methodology to classify every trade into the correct category as defined by ESMA. These categories are highly specific and include, for example:
   • Equities ▴ Tick size liquidity bands 5 and 6 (liquid shares)
   • Equities ▴ Tick size liquidity bands 3 and 4
   • Equities ▴ Tick size liquidity bands 1 and 2 (illiquid shares)
   • Exchange Traded Funds (ETFs)
   • Bonds
   • Interest Rate Derivatives
   • Credit Derivatives
4. Quantitative Analysis and Report Generation ▴ With the data sourced, cleansed, and classified, the firm can perform the quantitative analysis required for the RTS 28 report. This involves calculating the total volume and number of orders executed on each venue for each instrument class to identify the top five. Following this, the firm must prepare the qualitative summary of the execution quality obtained, referencing the analysis of RTS 27 data and internal monitoring. The final report is then compiled in the prescribed format, ready for public disclosure.
5. Monitoring and Review ▴ The process does not end with the publication of the report. The data and analysis should be fed back into the firm’s governance structure. A Best Execution Committee or similar body should review the findings to assess the effectiveness of the firm’s execution arrangements and make data-driven decisions to optimize them. This closes the loop and ensures the process drives continuous improvement.

Quantitative Modeling and Data Analysis

The heart of the reporting process is the quantitative analysis of execution data. This requires not only calculating the required metrics but also understanding their implications. The RTS 27 reports from venues provide a wealth of information that must be modeled and analyzed to inform a firm’s execution strategy. The table below illustrates a subset of the detailed data points a venue must provide in an RTS 27 report for a specific equity.

Detailed RTS 27 Data Example for a Single Equity

An investment firm would analyze this data across multiple venues to make informed routing decisions. For example, a lower effective spread on one venue suggests better price improvement opportunities. A firm’s quantitative models would weigh these factors based on its execution policy to determine the optimal venue for a given order.

Predictive Scenario Analysis

To illustrate the practical application of this framework, consider the case of “Alpha Hound Capital,” a mid-sized asset manager. Their Head of Trading, Anya Sharma, and Compliance Officer, David Chen, are conducting their annual review of the firm’s RTS 28 report data.

During the review, David points out an anomaly. For the “Equities ▴ Tick size liquidity bands 3 and 4” category, one of their top five venues, “MTF-Gamma,” shows a significantly higher average transaction cost compared to the other top venues, despite being the second-most used venue by volume. The firm’s execution policy for this asset class prioritizes total consideration (price plus cost), making this a red flag.

Anya pulls the underlying execution data. The raw data confirms David’s finding. While MTF-Gamma offered marginal price improvement, the execution fees were consistently higher, eroding the benefit.

Anya’s initial hypothesis is that the firm’s Smart Order Router (SOR) logic might be overweighting the price improvement factor without adequately penalizing the higher cost structure of MTF-Gamma. The SOR’s algorithm was designed to seek out small price improvements, but it seemed the model’s cost sensitivity parameter was set too low for this specific asset class when interacting with that venue’s fee schedule.

To test this, Anya’s team runs a simulation using the past six months of order flow data. They create two scenarios. Scenario A uses the existing SOR logic. Scenario B uses a recalibrated logic with an increased cost sensitivity parameter for MTF-Gamma.

The simulation projects the total execution cost under both scenarios. The results are stark. The recalibrated model in Scenario B would have saved the firm’s clients an estimated €250,000 in execution costs over the six-month period by routing a greater proportion of orders to “MTF-Delta,” which had slightly less price improvement but significantly lower all-in costs.

Armed with this quantitative evidence, Anya and David present their findings to the Best Execution Committee. The committee approves a change to the SOR’s routing logic for that specific asset class. In the firm’s next RTS 28 report, they can provide a concrete example of their monitoring process in action. The report’s qualitative summary would state:

“Our continuous monitoring of execution quality, as mandated by our Best Execution Policy, identified that for mid-cap equities, the cost component of execution on MTF-Gamma was negatively impacting the total consideration for our clients. Following a detailed quantitative analysis and simulation of alternative routing strategies, we adjusted our execution logic in Q3 to prioritize venues with a more favorable all-in cost profile for this asset class. This demonstrates our commitment to using execution data to dynamically optimize outcomes for our clients.”

This scenario highlights how the reporting framework, when executed properly, becomes a powerful tool for self-assessment and improvement, directly benefiting clients and strengthening the firm’s operational integrity.

System Integration and Technological Architecture

The entire reporting and analysis framework rests on a foundation of robust technological architecture and seamless system integration. A firm cannot meet its obligations without the right systems in place to capture, store, process, and analyze vast quantities of data.

The core of this architecture is typically a centralized data repository, often a data warehouse or a data lake. This repository must ingest data from multiple sources in real-time or near-real-time:

• Order and Execution Management Systems (OMS/EMS) ▴ These systems are the primary source of internal order and trade data. Integration is often achieved through direct database connections or, more commonly, through the Financial Information eXchange (FIX) protocol. Specific FIX tags (e.g. Tag 11 for ClOrdID, Tag 30 for LastMkt, Tag 39 for OrdStatus) are captured to build a complete picture of the order lifecycle.
• Market Data Feeds ▴ To calculate metrics like price improvement, the firm needs access to historical and real-time market data (e.g. the European Best Bid and Offer) from a consolidated tape provider or a direct feed from the venues.
• Reference Data Systems ▴ These systems provide the necessary information to classify instruments correctly by linking ISINs to asset classes, liquidity bands, and other regulatory attributes.
• Third-Party Data Sources ▴ This includes the RTS 27 reports published by execution venues, which need to be systematically downloaded, parsed (often from XML or CSV formats), and loaded into the data repository for analysis.

Once the data is centralized, a powerful analytics engine is required to perform the complex calculations, aggregations, and simulations described previously. This may involve a combination of SQL queries, Python or R scripts for statistical analysis, and business intelligence (BI) tools for visualization and reporting. The output of this engine is the formatted RTS 28 report and the internal management information dashboards used by the trading and compliance teams to monitor execution quality on an ongoing basis. The entire workflow, from data ingestion to report generation, must be automated, auditable, and resilient to ensure timely and accurate reporting.

Reflection

The Mandate beyond the Report

The operational and technical architecture required to fulfill MiFID II reporting obligations represents a significant institutional investment. The process forces a level of internal scrutiny that, while complex, provides an unvarnished view of a firm’s execution pathways. The produced reports are the final output, but the true value is generated within the machinery built to create them. The data repository, the analytical models, and the governance frameworks are assets of immense strategic potential.

Viewing this framework solely through the lens of regulatory compliance is a fundamental misinterpretation of its purpose. It is an operational mandate to build a system of intelligence. This system, once constructed, can be used not only to prove best execution but to actively discover it on a continuous basis. The insights gleaned from the data can inform algorithmic design, refine liquidity sourcing strategies, and provide a quantifiable basis for negotiating with execution venues.

The ultimate objective is the institutionalization of a data-driven culture where every execution decision is informed, measured, and optimized. The report is the evidence; the underlying system is the capability.