How Do Rts 27 and Rts 28 Reports Provide Evidence of Best Execution for Anonymous Rfqs? ▴ Question

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Concept

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The Mandate for Verifiable Execution

The principle of best execution is a foundational pillar of market integrity, representing a fiduciary compact between an investment firm and its clients. This duty requires firms to take all sufficient steps to obtain the best possible result for their clients, considering a spectrum of factors that extend beyond simple price metrics. Within the European Union’s Markets in Financial Instruments Directive (MiFID II) framework, this obligation was codified through a set of detailed reporting standards, notably the Regulatory Technical Standards (RTS) 27 and 28.

These reports were engineered to cast light on the often-opaque processes of trade execution, creating a public ledger of performance intended to foster competition among venues and empower investors with transparent data. An investment firm’s adherence to this mandate is a continuous, demonstrable process, not a static state of compliance.

RTS 27 reports originate from execution venues themselves ▴ such as regulated markets, multilateral trading facilities (MTFs), and systematic internalisers (SIs). Each venue was required to publish quarterly, granular data on execution quality for every financial instrument traded. These reports contained a mosaic of metrics, including details on prices, costs, and the speed and likelihood of execution. The design was to create a standardized, comparable dataset across the entire market, allowing participants to objectively assess the quality of different liquidity pools.

This data forms a public baseline, a quantitative backdrop of what is achievable in the open market under various conditions. It serves as a crucial reference point for all subsequent analysis of execution quality.

RTS 27 and 28 reports establish a data-driven framework for proving best execution by creating a public baseline for venue performance and requiring firms to justify their execution choices against it.

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The Conundrum of the Anonymous RFQ

Contrasting with the public nature of lit market data is the Request for Quote (RFQ) protocol, a vital mechanism for institutional participants, particularly when executing large or illiquid trades. An anonymous RFQ allows a firm to solicit quotes from a select group of liquidity providers without revealing its identity or the full size of its intended trade until the point of execution. This discretion is a powerful tool for minimizing information leakage and reducing market impact, which are critical components of achieving the best overall result for a client.

The process is inherently bilateral and off-book, creating a direct challenge to the transparency paradigm. The central question becomes ▴ how does a firm prove it achieved a superior outcome in a private negotiation when the primary regulatory tools are designed to measure public market activity?

This is where the function of the RTS 27 and 28 reports becomes a matter of analytical discipline. While the formal obligation to publish these specific reports has been suspended in the UK and deprioritized in the EU, the underlying legal requirement for firms to evidence their best execution process remains absolute. The data points and analytical logic prescribed by the RTS framework persist as the accepted methodology for this validation. For an anonymous RFQ, the evidence of best execution is constructed by using the public data from RTS 27 as a sophisticated benchmark.

The firm must build a case demonstrating that the execution achieved through the discreet RFQ process was quantitatively and qualitatively superior to the probable outcome had the order been routed to one or more public venues during the same period. The RTS 28 report, in turn, was the designated forum for the firm to articulate this analysis, summarizing its execution strategies and justifying why a venue, including its own RFQ protocol, was chosen. It is the narrative that connects the firm’s actions to its fiduciary duty, using the market-wide data as its evidentiary foundation.

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Strategy

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RTS 27 the Public Market Ledger

The strategic utility of RTS 27 data lies in its function as a comprehensive, multi-dimensional benchmark of market quality. It provides the raw material for a rigorous, evidence-based comparison of execution venues. For an investment firm, this data is the objective standard against which all its execution decisions, including those made via private protocols, are measured. The report is not a single document but a collection of detailed tables, each illuminating a different facet of execution performance.

A firm’s strategy for leveraging this information involves aggregating these disparate data points to construct a holistic picture of the available liquidity and execution quality across the market at any given time. This allows for a precise, data-driven evaluation of its own performance.

The core components of an RTS 27 report provide the necessary inputs for this comparative analysis. Understanding these components is fundamental to appreciating how they form the basis for evidencing best execution. The data allows a firm to answer critical questions ▴ What was the prevailing market price? What were the explicit and implicit costs of trading?

How quickly could an order have been executed elsewhere? What was the probability of execution for an order of a certain size? The answers to these questions form the quantitative backbone of any best execution analysis.

Key Data Categories within RTS 27 Reports
Data Category	Description	Strategic Implication for RFQ Analysis
Price Information	Includes intra-day and end-of-day price details, such as best bid and offer, volume-weighted average prices (VWAP), and the highest and lowest executed prices for a given instrument.	Provides the primary benchmark for assessing price improvement. The RFQ execution price is directly compared against the VWAP and other price metrics from lit venues.
Cost Disclosures	Details all explicit costs associated with executing on the venue, including execution fees, clearing fees, and any applicable taxes.	Allows for a “total cost” comparison. The net price of the RFQ (execution price adjusted for any fees) can be compared to the potential total cost on public venues.
Speed of Execution	Provides data on the time elapsed between an order being received and its execution, typically measured in milliseconds.	While less critical for patient, large-in-scale RFQ orders, it provides context on market conditions and the firm’s ability to access liquidity quickly if needed.
Likelihood of Execution	Contains information on the number and volume of orders executed versus those that were cancelled or expired, providing insight into the probability of filling an order of a certain size.	This is a critical factor for justifying RFQs. It helps to argue that attempting to execute a large order on a public venue could have resulted in partial fills and adverse market movement.

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RTS 28 the Firm’s Execution Narrative

If RTS 27 provides the market-wide data, the RTS 28 report is the firm’s opportunity to present its own analysis and justify its execution strategy. This annual report requires firms to disclose their top five execution venues for each class of financial instrument and to provide a summary of the execution quality obtained. The strategic purpose of this report is to compel firms to actively monitor and review their execution arrangements and to be able to articulate a coherent and defensible rationale for their choices. It is the formal mechanism for demonstrating that the firm has a robust process for fulfilling its best execution duty.

For anonymous RFQs, the RTS 28 report is where the firm connects its use of this off-book protocol to its overarching best execution policy. The firm must explain why, for certain types of orders, routing to a discreet liquidity pool via an RFQ is the “sufficient step” taken to achieve the best result. This involves a qualitative and quantitative summary.

The quantitative part relies on the benchmarking analysis against RTS 27 data, while the qualitative part addresses factors that are not easily captured in the data, such as the minimization of information leakage and the management of counterparty relationships. The report must demonstrate a thoughtful and systematic approach to venue selection.

Venue Selection Process ▴ The firm must outline the criteria used to select its top execution venues. For RFQs, this would include the quality and competitiveness of the liquidity providers in its network.
Execution Quality Summary ▴ A detailed analysis of the execution performance achieved. This is where the comparison against RTS 27 benchmarks would be presented, showing evidence of price improvement or cost savings.
Qualitative Factors ▴ An explanation of how qualitative elements influenced the execution strategy. For an anonymous RFQ, the primary justification is often the reduction of market impact, a factor that is paramount for large orders.
Conflict of Interest Management ▴ The report must also address how the firm manages any potential conflicts of interest in its execution process, ensuring that client orders are always prioritized.

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Execution

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Constructing the Evidentiary Bridge

The execution of a best execution analysis for an anonymous RFQ is a forensic process of data assembly and comparative analytics. It involves creating an evidentiary bridge between a private, bilateral trade and the public market. The core task is to use the aggregated, standardized data from RTS 27 reports as a control variable to assess the specific outcome of the RFQ.

This process moves beyond a simple check-the-box compliance exercise into the realm of sophisticated transaction cost analysis (TCA). A compliance officer or head of trading must reconstruct the market conditions at the time of the RFQ and model the probable outcomes of alternative execution strategies.

This analytical rigor is necessary because of the inherent tension between the RFQ’s opacity and the regulator’s demand for transparency. A simple assertion that the RFQ was “better” is insufficient. The firm must produce quantitative evidence. The process begins with the careful collection and normalization of RTS 27 data from all relevant trading venues for the specific instrument in question.

This forms the master benchmark dataset. Then, for each significant RFQ execution, a specific, time-sensitive analysis is performed, comparing the single RFQ result against the aggregated market data. The objective is to build an irrefutable case that the chosen execution method was in the client’s best interest.

The practical application of RTS principles involves a rigorous comparison of a private RFQ’s execution metrics against a composite benchmark of public market data from the same period.

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A Hypothetical Case Study a Corporate Bond Block Trade

Consider a scenario where an asset manager needs to sell a €15 million block of a specific corporate bond. Executing this trade on the lit market could alert other participants, leading to adverse price movements before the full order is filled. The trader therefore opts for an anonymous RFQ, soliciting quotes from five selected dealers. The best quote is hit, and the trade is executed.

Now, the firm must prove this was the best course of action. The following tables illustrate the data used in this process.

Table 1 ▴ Anonymous RFQ Execution Details
Parameter	Value
Financial Instrument	XYZ Corp 4.5% 2030 Bond
Trade Direction	Sell
Nominal Value	€15,000,000
Execution Timestamp	14:32:15 GMT
Execution Price	101.55
Explicit Costs (per million)	€50
Net Price	101.545

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The Comparative Analysis

To validate this execution, the firm’s compliance function constructs a benchmark from the RTS 27 data published by the three main venues where this bond trades. The analysis focuses on the 15-minute window surrounding the RFQ execution to ensure a relevant comparison.

Table 2 ▴ Composite Market Benchmark (Derived from RTS 27 Data) Time Window ▴ 14:25 – 14:40 GMT
Metric	Venue A (MTF)	Venue B (MTF)	Venue C (SI)
Average Quoted Bid Price	101.50	101.51	101.52
Average Quoted Offer Price	101.60	101.61	101.62
Volume-Weighted Avg. Price (VWAP)	101.54	101.56	N/A (Quote-driven)
Total Executed Volume (Sell)	€4,500,000	€3,200,000	€1,800,000
Average Order Size	€500,000	€400,000	€600,000

The analysis would proceed as follows:

Price Comparison ▴ The RFQ’s execution price of 101.55 is superior to the average quoted bid price on all three venues. It is also higher than the VWAP on Venue A (101.54). While slightly below the VWAP on Venue B (101.56), the analysis must consider the other factors.
Market Impact Assessment ▴ The total sell volume across all three public venues during the 15-minute window was €9.5 million. The firm’s order of €15 million was significantly larger than the combined market appetite. Attempting to execute this on the lit markets would have likely exhausted the available bids, pushing the price down significantly and resulting in a much lower average execution price. The RFQ protocol allowed the entire block to be executed at a single price, thus avoiding this substantial market impact.
Likelihood of Execution ▴ Given the average order sizes on the public venues, executing a €15 million order would have required breaking it into at least 25-30 smaller “child” orders. This would have increased operational complexity and the risk of information leakage. The RTS 27 data on likelihood of execution would further support the argument that an order of this magnitude had a low probability of being filled in its entirety without significant price concession on the lit market.

This detailed, data-driven comparison forms the core of the evidence. It demonstrates that the firm considered all relevant factors and that the decision to use an anonymous RFQ was not just a matter of convenience but a calculated strategy to protect the client’s interests by securing a better price and, crucially, avoiding the high implicit cost of market impact. This entire analytical narrative is what would be summarized in the firm’s RTS 28 report, providing a complete and defensible audit trail of its adherence to the best execution mandate.

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References

European Securities and Markets Authority. “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 concerning the data to be published by execution venues on the quality of execution of transactions.” Official Journal of the European Union, 2017.
European Securities and Markets Authority. “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.” Official Journal of the European Union, 2017.
Harris, Larry. Trading and Exchanges ▴ Market Microstructure for Practitioners. Oxford University Press, 2003.
Financial Conduct Authority. “Markets in Financial Instruments Directive II (MiFID II) Implementation ▴ Policy Statement II.” PS17/14, July 2017.
O’Hara, Maureen. Market Microstructure Theory. Blackwell Publishers, 1995.
Gomber, Peter, et al. “High-Frequency Trading.” Goethe University Frankfurt, Working Paper, 2011.
The TRADE. “Best execution under the microscope.” The TRADE Magazine, Issue 50, Q2 2017.
Deloitte. “MiFID II – Best execution.” Deloitte Insights, 2018.

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From Regulatory Data to Systemic Intelligence

The framework established by RTS 27 and 28, even with its formal reporting requirements in flux, compels a fundamental shift in perspective. It moves the concept of best execution from a qualitative ideal to a quantitative discipline. The data provides a common language for discussing and evaluating execution quality, forcing a level of analytical rigor that benefits the entire market ecosystem. For the institutional participant, the true value lies not in the act of filing a report, but in the internal capabilities that must be built to generate it.

Developing the capacity to ingest, normalize, and analyze this vast amount of market data is to build a system of intelligence. It provides a near real-time map of market liquidity and performance. This capability, born from a regulatory mandate, becomes a distinct strategic asset.

It allows a firm to make more informed routing decisions, to negotiate more effectively in RFQ protocols, and to provide clients with a truly transparent and verifiable accounting of their execution outcomes. The ultimate result is a more robust, resilient, and data-driven operational framework, which is the cornerstone of achieving a consistent and defensible edge in modern financial markets.