How Does MiFID II Specifically Define the Requirements for Best Execution Reporting?

Concept

Your question regarding how MiFID II defines best execution reporting touches upon a critical piece of market architecture, one designed to systematically embed transparency into the European financial system. The regulation approached this not as a single mandate, but as a dual-pronged engineering problem, creating two distinct reporting frameworks known as Regulatory Technical Standard 27 (RTS 27) and Regulatory Technical Standard 28 (RTS 28). The core design was to generate a complete circuit of information. RTS 27 was the responsibility of the execution venues ▴ the exchanges, multilateral trading facilities (MTFs), and systematic internalisers (SIs) ▴ compelling them to publish vast, standardized quarterly data sets on the quality of their execution.

This was the supply side of the transparency equation. Concurrently, RTS 28 targeted the investment firms, the buy-side, requiring them to annually disclose the top five venues they used for executing client orders and to provide a qualitative assessment of the execution quality achieved. This was the demand-side feedback loop.

The fundamental principle was to create a market-wide system of accountability through data. The theory held that by forcing venues to publish comparable metrics on price, cost, speed, and likelihood of execution, and by requiring firms to report on which venues they utilized, clients and regulators could make informed judgments. An investor could, in principle, analyze an RTS 27 report from an exchange and compare it to the RTS 28 report from their asset manager to ask a pointed question ▴ why was a particular venue chosen when its own data suggested suboptimal performance on a key metric? This system was an ambitious attempt to codify and quantify the abstract legal duty of “best execution” into a set of verifiable, machine-readable outputs.

However, the operational reality of this architecture led to its eventual deprecation. Both the UK and the EU have suspended these specific reporting obligations. The system produced a deluge of data that was so voluminous and complex that it was rarely used by its intended audience, the end clients. Meaningful comparisons proved difficult.

The core regulatory principle, the legal and fiduciary duty for a firm to secure the best possible outcome for its clients when executing orders, remains absolutely central to the MiFID II framework. The focus has simply shifted from a rigid, public reporting structure to a more principles-based approach, where firms must maintain a robust internal execution policy and be prepared to demonstrate, through their own internal transaction cost analysis (TCA) and governance processes, that they are systemically achieving best execution. The architectural blueprint for transparency reporting has been archived, but the foundational mandate it was built to serve is more intensely scrutinized than ever.

Strategy

The strategic intent behind MiFID II’s best execution reporting was to replace ambiguity with evidence. The framework was architected to create a transparent marketplace where execution quality could be objectively measured and compared, shifting the conversation between investment firms and their clients from one based on trust to one based on verifiable data. This strategy was operationalized through the distinct, yet interconnected, mandates of RTS 27 and RTS 28.

RTS 27 the Venue Accountability Protocol

RTS 27 was the foundational layer of this strategy, targeting the source of execution. It mandated that all execution venues, from national exchanges to bank-run systematic internalisers, publish highly detailed quarterly reports. These reports were not qualitative summaries; they were granular, instrument-by-instrument data dumps designed for quantitative analysis. The goal was to create a standardized benchmark, allowing market participants to compare venues on a like-for-like basis across several key dimensions of execution quality.

The strategic objective of RTS 27 was to make execution quality a quantifiable and comparable commodity across all European trading venues.

The data required was extensive, covering price, costs, speed, and likelihood of execution for each financial instrument traded on the venue. For an equity instrument, for example, a venue would need to provide detailed information broken down by price, size, and time-of-day buckets. This allowed for a nuanced analysis of performance under different market conditions.

The table below provides a structured overview of the core data fields that were mandated under the RTS 27 framework. It illustrates the depth of information venues were required to disclose, forming the bedrock of the intended transparency regime.

RTS 28 the Investment Firm Disclosure Mandate

If RTS 27 provided the raw material for analysis, RTS 28 was the mechanism for demonstrating how that material was used. This regulation required investment firms to publish an annual report detailing the top five execution venues they used for each class of financial instrument. The report had to quantify the volume and number of client orders executed at each venue and disclose the percentage of aggressive (liquidity-taking) versus passive (liquidity-providing) orders. This quantitative disclosure was complemented by a qualitative summary explaining the firm’s execution strategy and how it had monitored and achieved best execution for its clients over the year.

The strategic purpose was twofold. First, it forced firms to explicitly justify their venue selection, creating a clear line of accountability to their clients. Second, it was intended to empower clients, giving them the information needed to challenge their providers’ execution choices. A client could, in theory, see that their firm routed 80% of its equity orders to a single venue and then use RTS 27 data to question if that venue truly offered the best results compared to its competitors.

The Strategic Shortcomings and the Pivot

While the architectural logic was sound, the practical implementation of this strategy revealed significant flaws. The sheer volume of data produced by RTS 27 reports made them unwieldy and difficult for all but the most sophisticated quantitative analysts to use. The reports were rarely accessed by the end investors they were designed to protect.

Furthermore, subtle differences in how venues calculated and presented the data made direct, meaningful comparisons challenging. Consequently, regulators in both the EU and UK concluded that the reporting obligations were not achieving their intended purpose and suspended them.

This suspension did not represent a retreat from the core principle. Instead, it marked a strategic pivot. The focus has shifted from public, standardized reporting to the firm’s internal, proprietary processes. The enduring strategy is now centered on the firm’s Order Execution Policy.

This document, and the governance and data analysis that support it, is now the primary mechanism through which a firm must demonstrate its commitment to the best execution principle. The burden of proof has moved from public disclosure to internal diligence, requiring firms to build and maintain their own robust systems for monitoring, analyzing, and evidencing the quality of their execution. The strategy is now less about populating a public database and more about cultivating an internal culture of continuous, data-driven improvement in execution quality.

Execution

With the decommissioning of the RTS 27 and RTS 28 reporting regimes, the execution of the best execution mandate under MiFID II has evolved. The focus has pivoted from a prescriptive, public disclosure framework to a principles-based obligation that demands robust internal systems, rigorous data analysis, and demonstrable governance. For an institutional trading desk, this means that the process of achieving and evidencing best execution is now an internally managed, continuous cycle of analysis, action, and review. The following sections provide an operational playbook for this new environment.

The Operational Playbook an Enduring Framework

A firm’s Order Execution Policy is the central nervous system of its best execution framework. It is a dynamic document that must be meticulously designed, implemented, and reviewed. The following steps outline a comprehensive operational process:

1. Define and Weight Execution Factors The process begins with identifying the full spectrum of execution factors as outlined by MiFID II. For each class of financial instrument, the firm must determine the relative importance of these factors.
   • Price The ultimate price at which an asset is bought or sold.
   • Costs All explicit expenses, including venue fees, clearing and settlement costs, and any applicable taxes.
   • Speed The latency between order transmission and execution confirmation.
   • Likelihood of Execution and Settlement The certainty that an order will be filled and that the trade will settle without failure.
   • Size and Nature of the Order The impact of a large or complex order on the market and the ability of a venue to handle it.
2. Systematic Venue and Broker Selection The firm must establish a formal process for selecting, reviewing, and monitoring the execution venues and brokers it uses. This involves initial due diligence and ongoing performance analysis based on quantitative data.
3. Pre-Trade Analysis and Strategy Selection Before an order is placed, a pre-trade analysis should be conducted to determine the optimal execution strategy. This involves using historical data and market intelligence to forecast potential transaction costs and market impact.
4. Execution and Monitoring During the execution process, orders must be monitored in real-time to ensure they are performing in line with the chosen strategy. This may involve adjusting algorithmic parameters or switching execution venues in response to changing market conditions.
5. Post-Trade Transaction Cost Analysis (TCA) This is the critical feedback loop. Every execution must be analyzed to measure its quality against various benchmarks. The results of this analysis feed back into the pre-trade and venue selection processes, creating a cycle of continuous improvement.

Quantitative Modeling and Data Analysis

In the absence of RTS 27 and 28, the burden of proof for best execution falls on the firm’s internal Transaction Cost Analysis (TCA). A sophisticated TCA function is the cornerstone of a defensible best execution policy. It requires a robust data infrastructure and a clear analytical methodology.

A firm’s internal TCA capability is the definitive tool for validating its adherence to the best execution mandate in the current regulatory climate.

The analysis begins with capturing raw trade data, which is then processed to calculate various performance metrics against industry-standard benchmarks. The table below illustrates a simplified example of the raw data captured for a series of trades.

This raw data is then enriched with market data to calculate performance metrics. The following table demonstrates how these trades would be analyzed, calculating slippage against key benchmarks like the arrival price (the market price at the moment the order was received by the trading desk) and the Volume-Weighted Average Price (VWAP).

This analysis allows the firm to move beyond simple cost measurement to a nuanced understanding of execution quality, answering critical questions. Which venues provide the best performance for aggressive, liquidity-taking orders? Which are better for passive, spread-capturing strategies? The aggregation of this data provides a powerful tool for optimizing the firm’s execution strategy over time.

Predictive Scenario Analysis

Consider a portfolio manager at a long-only asset manager who needs to purchase 1.5 million shares of a mid-cap technology stock, representing 25% of its average daily volume. A simple market order would create significant market impact, driving up the purchase price. The Head of Trading must devise a strategy to minimize this impact and demonstrate that the execution was optimal.

The process begins with pre-trade analysis. The trading desk uses its internal TCA system, which contains historical data on all previous trades in this stock and its peers. The system models the expected market impact of various execution algorithms. A VWAP algorithm, which aims to match the volume-weighted average price over the course of the day, is modeled to have a likely impact of 8 basis points.

A more sophisticated implementation shortfall algorithm, which becomes more aggressive when prices are favorable, is modeled to have a potential impact of 5 basis points, but with higher volatility of outcomes. The analysis also considers venue performance, noting that for this particular stock, a combination of the primary exchange and two specific MTFs has historically resulted in the lowest impact for passive orders.

Based on this data, the Head of Trading selects the implementation shortfall algorithm, with an instruction to limit participation to 15% of the traded volume at any given time to avoid signaling its intent to the market. The order is routed primarily to the three selected venues. Throughout the day, the trading desk monitors the execution in real-time. They notice that another large seller has entered the market, causing the price to trend downwards.

The algorithm, as designed, increases its participation rate to take advantage of the favorable price movement. The real-time TCA dashboard shows that the execution is currently outperforming the arrival price benchmark by 3 basis points.

At the end of the day, the full 1.5 million shares have been purchased. The post-trade TCA report is automatically generated. The final execution price is 4.5 basis points better than the arrival price and 2 basis points better than the interval VWAP. The report breaks down performance by venue, confirming that the chosen venues did indeed provide superior execution quality.

This report is then provided to the portfolio manager and archived for the firm’s compliance committee. It serves as a definitive, data-driven record that the firm not only sought but demonstrably achieved the best possible outcome for its client, fulfilling its MiFID II obligation in a robust and quantifiable manner.

System Integration and Technological Architecture

Executing this level of analysis requires a sophisticated and integrated technology stack. The Order Management System (OMS) serves as the system of record for all client orders. When an order is ready for execution, it is passed to the Execution Management System (EMS). The EMS is the trader’s cockpit, providing connectivity to various execution venues and housing the suite of execution algorithms.

The communication between these systems, and with the outside world, is governed by the Financial Information eXchange (FIX) protocol. Specific FIX tags are crucial for the best execution process. For example, when an order is sent to a venue, Tag 11 (ClOrdID) provides a unique identifier that is used to track the order throughout its lifecycle.

When executions come back, Tag 30 (LastMkt) identifies the venue, and Tag 39 (OrdStatus) confirms the state of the order. This data is captured and fed into a centralized data warehouse.

This data warehouse is the heart of the TCA system. It must be capable of storing vast amounts of information, including every order, execution, and tick-by-tick market data for the relevant instruments. APIs are used to feed this warehouse with data from various sources and to provide other systems with access to the TCA results. This integrated architecture ensures that the data required for best execution analysis is captured accurately and is available to the traders, portfolio managers, and compliance officers who need it to make informed decisions and to satisfy their regulatory obligations.

Reflection

What Does Your Execution Data Reveal about Your Strategy

The transition away from the prescriptive reporting of RTS 27 and RTS 28 places the analytical burden squarely within the firm. The question shifts from “Have we filed the correct report?” to “Is our internal execution framework fundamentally sound and perpetually improving?” The data generated by your trading desk is a strategic asset. It contains the unfiltered truth of your execution quality. Viewing this data not as a compliance artifact but as the primary input for a dynamic feedback loop is the critical distinction.

How does your current technological architecture support this continuous analysis? Does it merely record what happened, or does it provide the intelligence to systematically refine what will happen next? The ultimate execution advantage lies in the ability to transform your own transactional data into a predictive and adaptive tool.