What Are the Key Differences in Applying Rts 24 to Lit Order Books versus Rfq Systems? ▴ Question

A stylized abstract radial design depicts a central RFQ engine processing diverse digital asset derivatives flows. Distinct halves illustrate nuanced market microstructure, optimizing multi-leg spreads and high-fidelity execution, visualizing a Principal's Prime RFQ managing aggregated inquiry and latent liquidity

A smooth, off-white sphere rests within a meticulously engineered digital asset derivatives RFQ platform, featuring distinct teal and dark blue metallic components. This sophisticated market microstructure enables private quotation, high-fidelity execution, and optimized price discovery for institutional block trades, ensuring capital efficiency and best execution

Concept

The application of Regulatory Technical Standard 24 (RTS 24) presents a nuanced set of obligations for trading venues, with material distinctions in its implementation across different market structures. The core of RTS 24 is the mandate for trading venues to maintain a detailed and time-stamped record of every order and its lifecycle. This requirement, while seemingly straightforward, has profoundly different implications when applied to the transparent, continuous environment of a lit order book compared to the discreet, bilateral nature of a Request for Quote (RFQ) system. Understanding these differences is fundamental to designing a compliant and efficient trading infrastructure.

A transparent sphere, representing a granular digital asset derivative or RFQ quote, precisely balances on a proprietary execution rail. This symbolizes high-fidelity execution within complex market microstructure, driven by rapid price discovery from an institutional-grade trading engine, optimizing capital efficiency

The Divergence in Data Capture

For a lit order book, RTS 24 compliance centers on the capture of a continuous stream of order events. Every new order, modification, cancellation, and execution must be recorded with a high degree of granularity. This includes not just the price and quantity, but also the timestamps of each event, the type of order, and the identity of the market participant. The data generated is voluminous and requires a robust and scalable infrastructure to manage.

In contrast, an RFQ system operates on a discontinuous basis. The data capture process is initiated by a specific request for a quote from a client. The subsequent data points to be recorded under RTS 24 include the initial request, the quotes received from liquidity providers, the execution of the chosen quote, and the identities of all parties involved. While the volume of data may be lower than in a lit order book, the complexity lies in linking the various stages of the RFQ process into a coherent and auditable trail.

A lit order book generates a continuous stream of data points, while an RFQ system produces discrete data sets tied to specific requests.

Robust metallic beam depicts institutional digital asset derivatives execution platform. Two spherical RFQ protocol nodes, one engaged, one dislodged, symbolize high-fidelity execution, dynamic price discovery

Implications for Transparency and Best Execution

The application of RTS 24 to both systems also has different implications for the principles of transparency and best execution. In a lit order book, the detailed order data required by RTS 24 provides a clear and auditable record of the price formation process. This allows regulators to monitor for market abuse and to assess whether firms are meeting their best execution obligations.

For RFQ systems, the RTS 24 data provides a different kind of transparency. It allows for the verification that a firm has solicited quotes from a sufficient number of liquidity providers and has executed the trade at the best available price among the quotes received. This is a critical component of demonstrating best execution in a less transparent trading environment.

A sleek, cream-colored, dome-shaped object with a dark, central, blue-illuminated aperture, resting on a reflective surface against a black background. This represents a cutting-edge Crypto Derivatives OS, facilitating high-fidelity execution for institutional digital asset derivatives

A dynamic visual representation of an institutional trading system, featuring a central liquidity aggregation engine emitting a controlled order flow through dedicated market infrastructure. This illustrates high-fidelity execution of digital asset derivatives, optimizing price discovery within a private quotation environment for block trades, ensuring capital efficiency

Strategy

A strategic approach to RTS 24 compliance requires a deep understanding of how the regulation interacts with the specific mechanics of each trading system. For both lit order books and RFQ systems, the goal is to build a compliance framework that is not only robust and auditable but also efficient and scalable. This involves a careful consideration of data management, system architecture, and the integration of compliance processes into the overall trading workflow.

Luminous blue drops on geometric planes depict institutional Digital Asset Derivatives trading. Large spheres represent atomic settlement of block trades and aggregated inquiries, while smaller droplets signify granular market microstructure data

Data Management Strategies

The sheer volume of data generated by a lit order book necessitates a sophisticated data management strategy. This includes the use of high-performance databases, efficient data storage solutions, and automated data validation processes. A key strategic consideration is the ability to retrieve and analyze large datasets in a timely manner, both for internal compliance monitoring and for responding to regulatory requests.

For RFQ systems, the data management strategy is more focused on the logical linking of data points. The challenge is to create a unified record of each RFQ transaction, from the initial request to the final execution. This requires a system that can capture and store data from multiple sources, including the client’s order management system, the RFQ platform, and the systems of the liquidity providers.

A chrome cross-shaped central processing unit rests on a textured surface, symbolizing a Principal's institutional grade execution engine. It integrates multi-leg options strategies and RFQ protocols, leveraging real-time order book dynamics for optimal price discovery in digital asset derivatives, minimizing slippage and maximizing capital efficiency

Comparative Data Management Approaches

Feature	Lit Order Book	RFQ System
Data Volume	High and continuous	Lower and event-driven
Data Structure	Homogeneous and time-series based	Heterogeneous and transactional
Key Challenge	Managing data volume and velocity	Linking disparate data points

Abstract geometric design illustrating a central RFQ aggregation hub for institutional digital asset derivatives. Radiating lines symbolize high-fidelity execution via smart order routing across dark pools

System Architecture Considerations

The system architecture for RTS 24 compliance should be designed to be both resilient and adaptable. For lit order books, this means a system that can handle high throughput and low latency, with built-in redundancy and failover capabilities. The architecture should also be able to accommodate future increases in data volume and changes in regulatory requirements.

For RFQ systems, the architecture should be designed to support the end-to-end workflow of an RFQ transaction. This includes the ability to integrate with various internal and external systems, as well as the flexibility to support different RFQ protocols and asset classes. A modular architecture can be particularly effective, allowing for the easy addition of new features and functionalities.

The system architecture for RTS 24 compliance must be tailored to the specific data and workflow characteristics of each trading system.

A precision instrument probes a speckled surface, visualizing market microstructure and liquidity pool dynamics within a dark pool. This depicts RFQ protocol execution, emphasizing price discovery for digital asset derivatives

A deconstructed mechanical system with segmented components, revealing intricate gears and polished shafts, symbolizing the transparent, modular architecture of an institutional digital asset derivatives trading platform. This illustrates multi-leg spread execution, RFQ protocols, and atomic settlement processes

Execution

The execution of an RTS 24 compliance program requires a detailed and granular approach to data capture, storage, and reporting. The specific data fields and reporting formats will differ between lit order books and RFQ systems, reflecting the fundamental differences in their operating models. A successful execution will depend on a clear understanding of these differences and the implementation of appropriate technological solutions.

A central, blue-illuminated, crystalline structure symbolizes an institutional grade Crypto Derivatives OS facilitating RFQ protocol execution. Diagonal gradients represent aggregated liquidity and market microstructure converging for high-fidelity price discovery, optimizing multi-leg spread trading for digital asset options

Data Fields for Lit Order Books

For lit order books, RTS 24 requires the capture of a comprehensive set of data fields for each order event. These fields are designed to provide a complete and auditable record of the order’s lifecycle, from its entry into the order book to its final execution or cancellation. The following table provides an overview of the key data fields required.

Abstract layers in grey, mint green, and deep blue visualize a Principal's operational framework for institutional digital asset derivatives. The textured grey signifies market microstructure, while the mint green layer with precise slots represents RFQ protocol parameters, enabling high-fidelity execution, private quotation, capital efficiency, and atomic settlement

Key RTS 24 Data Fields for Lit Order Books

Field	Description
Order ID	A unique identifier for the order.
Timestamp	The date and time of the order event, in UTC.
Event Type	The type of order event (e.g. new order, modification, cancellation, execution).
Instrument ID	The unique identifier of the financial instrument.
Price	The price of the order.
Quantity	The quantity of the order.

An institutional-grade platform's RFQ protocol interface, with a price discovery engine and precision guides, enables high-fidelity execution for digital asset derivatives. Integrated controls optimize market microstructure and liquidity aggregation within a Principal's operational framework

Data Fields for RFQ Systems

For RFQ systems, the data capture requirements of RTS 24 are focused on the different stages of the RFQ process. The goal is to create a complete record of the transaction, from the initial request for a quote to the final execution. The following list outlines the key data points to be captured.

Request ID ▴ A unique identifier for the RFQ request.
Client ID ▴ The identifier of the client making the request.
Instrument ID ▴ The unique identifier of the financial instrument.
Quantity ▴ The quantity of the instrument being requested.
Quote ID ▴ A unique identifier for each quote received.
Liquidity Provider ID ▴ The identifier of the liquidity provider submitting the quote.
Quote Price ▴ The price of the quote.
Execution Timestamp ▴ The date and time of the execution.

The specific data fields required by RTS 24 are tailored to the unique characteristics of each trading system, with a focus on providing a complete and auditable record of all trading activity.

Institutional-grade infrastructure supports a translucent circular interface, displaying real-time market microstructure for digital asset derivatives price discovery. Geometric forms symbolize precise RFQ protocol execution, enabling high-fidelity multi-leg spread trading, optimizing capital efficiency and mitigating systemic risk

References

Commission Delegated Regulation (EU) 2017/580 of 24 June 2016 supplementing Regulation (EU) No 600/2014 of the European Parliament and of the Council with regard to regulatory technical standards for the maintenance of relevant data relating to orders in financial instruments.
European Securities and Markets Authority. (2024). Consultation Paper on the Review of Regulatory Technical Standards on Transaction Data Reporting and on Order Book Data under the Revised Markets in Financial Instruments Regulation.
Financial Conduct Authority. (2017). Markets in Financial Instruments Directive II Implementation ▴ Policy Statement II.
International Organization of Securities Commissions. (2018). Regulatory Issues Raised by the Impact of Technological Changes on Market Integrity and Efficiency.
Jones, L. (2020). Market Microstructure and Regulatory Design. Oxford University Press.

Sharp, transparent, teal structures and a golden line intersect a dark void. This symbolizes market microstructure for institutional digital asset derivatives

Reflection

The implementation of RTS 24 is a complex undertaking, requiring a deep understanding of both the regulatory requirements and the specific characteristics of different trading systems. For firms operating in today’s increasingly complex and regulated markets, a strategic and well-executed compliance program is not just a matter of meeting regulatory obligations; it is a fundamental component of a robust and resilient trading infrastructure. By embracing a proactive and data-driven approach to compliance, firms can not only mitigate regulatory risk but also enhance their operational efficiency and strengthen their competitive position.