How Do Systematic Internalisers Impact Best Execution Strategy for Both Equities and Non-Equities? ▴ Question

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Concept

The operational mandate for any institutional trading desk is the effective sourcing of liquidity at the optimal price, a process encapsulated by the principle of best execution. The introduction of the Systematic Internaliser (SI) regime under MiFID II represents a fundamental architectural shift in how this mandate is fulfilled across European markets. An SI is an investment firm that deals on its own account by executing client orders outside of a regulated market or multilateral trading facility (MTF). This structure allows large dealers, typically banks, to internalize order flow, matching buy and sell orders from their clients against their own principal capital.

This development is a direct consequence of a regulatory architecture designed to formalize and increase transparency in the vast over-the-counter (OTC) space. For equities, the SI framework provided a regulated venue for principal liquidity following the prohibition of Broker Crossing Networks (BCNs). For non-equities, such as bonds and derivatives, the SI regime imposes a new degree of pre-trade transparency and systematic rigor on markets that have historically operated with greater opacity.

The core function of an SI is to provide a bilateral source of liquidity, where the SI itself is the counterparty to the client’s trade. This direct interaction model stands in contrast to the multilateral, all-to-all model of a traditional lit exchange.

Systematic Internalisers function as private liquidity pools where investment firms execute client orders against their own capital, fundamentally altering the pathways to achieving best execution.

The impact on market structure is profound. It creates a regulated bifurcation of liquidity. On one side, there are the traditional lit markets (exchanges) with central limit order books offering multilateral price discovery. On the other, a network of SIs offers bilateral, principal-based liquidity.

A trading desk’s best execution strategy is therefore no longer a question of simply finding the best price on a single exchange. It has evolved into a complex optimization problem ▴ how to intelligently access and interact with these parallel sources of liquidity to minimize market impact, control information leakage, and secure price improvement, all while adhering to a rigorous, evidence-based execution policy.

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What Defines an SI’s Role in Market Structure?

An SI is defined by quantitative thresholds set by regulators, based on the frequency and volume of its principal trading activity in a specific instrument. If a firm’s OTC trading in a security crosses these thresholds, it is obligated to register as an SI for that instrument. Firms can also voluntarily “opt-in” to the SI regime for certain asset classes, which can be a strategic decision to attract order flow by offering clients simplified trade reporting and a reliable source of principal liquidity. This dual pathway to becoming an SI means that the landscape of available liquidity is dynamic.

The best execution obligation requires buy-side firms to be perpetually aware of which counterparties are SIs for which instruments, as this status dictates pre-trade transparency obligations and, crucially, who is responsible for post-trade reporting to the public via an Approved Publication Arrangement (APA). When trading with an SI, the reporting obligation falls to the SI, reducing the operational burden for the client.

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Strategy

The integration of Systematic Internalisers into the market fabric necessitates a complete re-architecting of best execution strategy. The process shifts from a simple search for the best displayed price to a multi-venue liquidity sourcing strategy that must intelligently weigh the distinct advantages and characteristics of both lit exchanges and SI counterparties. The core of this new strategy is the firm’s Smart Order Router (SOR), the algorithmic engine responsible for dissecting an order and routing its components to the optimal destinations.

An effective SOR must be calibrated to view SIs as a primary source of potential price improvement and reduced market impact. For equity orders, an SOR might first ping a network of SIs for a quote before exposing the order to the lit market. This is because SIs can offer execution at the midpoint of the lit market’s bid-ask spread or better, providing tangible price improvement without creating a visible footprint on the central limit order book. This discretion is a paramount strategic advantage when executing large orders, as it mitigates the risk of adverse price movements caused by signaling trading intent to the broader market.

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Strategic Frameworks for Equity Execution

For equities, the best execution strategy revolves around managing the trade-off between the certainty of execution on a lit market and the potential for price improvement and discretion offered by SIs. The overarching MiFID II best execution obligation requires firms to consider price, cost, speed, and likelihood of execution. SIs directly address these factors.

Price Improvement ▴ SIs are not bound by the same tick size increments as lit exchanges for certain trades. This allows them to offer prices that are marginally better than the European Best Bid and Offer (EBBO), providing quantifiable price improvement that must be documented in the execution policy.
Market Impact Reduction ▴ By internalizing a trade, an SI prevents the order from consuming liquidity from the public order book. This is a critical advantage for large “risk” orders where exposing the full size would likely move the market price against the trader. The SI absorbs the risk onto its own balance sheet.
Cost and Reporting Efficiency ▴ Trading with an SI simplifies the operational workflow. The SI assumes the responsibility for trade reporting, which lowers the administrative and compliance costs for the buy-side firm.

The following table provides a comparative analysis of strategic outcomes when executing a large-cap equity order through different channels.

Table 1 ▴ Comparative Execution Strategy for a 50,000 Share Equity Order
Execution Factor	Strategy 1 ▴ Lit Market Only (VWAP Algorithm)	Strategy 2 ▴ SI-Centric (SOR with SI Ping)	Strategic Outcome
Price Discovery	Contributes to public price discovery but is also fully exposed to it.	Leverages public price as a benchmark but does not directly impact it. Execution occurs based on a firm quote.	SI strategy minimizes information leakage, protecting the order’s intent.
Market Impact	High potential for market impact as the algorithm consumes liquidity from the order book over time.	Minimal to zero market impact, as the trade is internalized against the SI’s principal capital.	SI execution is superior for impact-sensitive orders.
Execution Price	Average price is benchmarked to the Volume-Weighted Average Price (VWAP) over the execution period.	Potential for execution at the midpoint of the spread or better, offering direct price improvement over the lit market quote.	SI offers a high probability of quantifiable price improvement.
Reporting Burden	The executing broker manages reporting, but the order’s “child” slices are visible on public feeds.	The SI assumes the full post-trade reporting obligation, simplifying operations for the client.	SI strategy reduces the client’s operational overhead.

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Adapting Strategy for Non-Equity Instruments

In non-equity markets like corporate bonds and derivatives, the strategic impact of SIs is arguably even more significant. These markets are traditionally less centralized and more reliant on bilateral relationships and Request for Quote (RFQ) protocols. The SI regime brings a layer of formalization and pre-trade transparency to this world.

For non-equity instruments, the SI regime transforms opaque, relationship-based trading into a more systematic and transparent process.

A key strategic shift is the ability to access firm, executable quotes from SIs in instruments that previously lacked reliable pre-trade price information. While recent regulatory updates in 2024 have removed some pre-trade transparency requirements for non-equity SIs to reduce complexity, the overall framework still pushes for greater structure. The best execution strategy here is to build an RFQ system that programmatically polls multiple SIs, alongside other liquidity providers, to create a competitive pricing environment. This systematizes the “shopping around” process and provides a clear audit trail to justify the choice of execution counterparty, which is a cornerstone of the best execution obligation.

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Execution

The execution of a trading strategy that incorporates Systematic Internalisers is a function of technological integration, rigorous counterparty analysis, and detailed transaction cost analysis (TCA). It moves the trading desk’s function from that of a simple order placer to a manager of a complex liquidity sourcing system. The operational playbook must be precise, data-driven, and continuously refined.

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How Should a Firm Integrate SI Liquidity?

Integrating SI liquidity into a best execution framework is a multi-stage process. It begins with due diligence and ends with post-trade analysis, forming a continuous feedback loop. A firm’s execution policy must clearly document each stage of this process to satisfy regulatory requirements.

Counterparty Due Diligence and Onboarding ▴ The first step is to identify and vet potential SI counterparties. This involves more than just their stated asset class coverage. The trading desk must assess the quality and reliability of their quoting, their typical response times to RFQs, and their fill rates. This analysis should be quantitative, tracking the frequency and magnitude of price improvement offered.
Technological Integration ▴ The firm’s Order Management System (OMS) and Execution Management System (EMS) must be technologically capable of interacting with SIs. This typically occurs via the FIX (Financial Information eXchange) protocol. The Smart Order Router (SOR) must be configured with logic that understands when and how to route orders to SIs. This includes rules for “pinging” SIs before, or in parallel with, routing to lit venues.
Pre-Trade Decision Making ▴ For each order, the execution strategy must be determined. For liquid equity orders below a certain size, the SOR might automatically access SIs. For larger, less liquid orders, a “high-touch” approach may be necessary, involving manual RFQs sent to a curated list of SIs known to specialize in that instrument.
Post-Trade Analysis and Policy Refinement ▴ After execution, every trade must be analyzed. TCA reports are essential for comparing the execution quality from SIs against lit market benchmarks (e.g. arrival price, VWAP). This data is then used to refine the SOR logic and the list of preferred SI counterparties. This is not a static process; it is a continuous cycle of performance measurement and optimization.

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Quantitative Analysis of Execution Quality

A robust TCA program is the definitive tool for measuring the effectiveness of an SI-inclusive execution strategy. The analysis must capture the explicit and implicit costs of trading. The table below illustrates a sample TCA report comparing execution venues for a basket of European equity trades.

Table 2 ▴ Transaction Cost Analysis (TCA) Report Sample
Execution Venue	Total Value Traded (€)	Average Price Improvement (bps)	Market Impact (bps vs. Arrival Price)	Reversion (bps)	Execution Speed (ms)
Lit Exchange A	15,000,000	N/A	+3.5	-1.0	50
MTF B	12,500,000	+0.2	+2.8	-0.8	75
Systematic Internaliser 1	25,000,000	+0.8	+0.5	-0.1	150
Systematic Internaliser 2	18,000,000	+0.6	+0.7	-0.2	180

This data provides actionable intelligence. The SIs are delivering significant price improvement and drastically reducing market impact compared to the lit venues. The slightly higher execution speed (latency) is an acceptable trade-off for these benefits.

The “Reversion” metric, which measures post-trade price movements against the trade direction, is also lower for SIs, suggesting less information leakage. Based on this analysis, the execution policy would be updated to preference SI 1 and SI 2 for this type of order flow.

A granular, data-driven TCA framework is the only mechanism to truly validate and optimize an execution strategy in a fragmented liquidity landscape.

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What Is the Future Regulatory Trajectory?

The regulatory environment governing SIs is not static. Regulators are continually monitoring the balance of trading between lit venues and SIs, concerned that excessive internalization could harm public price discovery. Future changes, such as forcing SIs to adhere to the public tick size regime for smaller trades, could alter the strategic calculus by reducing their ability to offer marginal price improvement.

Therefore, a core part of the execution function is regulatory intelligence ▴ understanding proposed changes and modeling their potential impact on the firm’s execution quality. This proactive stance allows the trading desk to adapt its systems and strategies before new rules come into force, maintaining its competitive edge.

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References

Gomber, Peter, et al. “Liquidity in the German stock market ▴ a comparison of Xetra, dark pools and broker-dealer crossing networks.” Financial Markets and Portfolio Management, vol. 30, no. 1, 2016, pp. 31-62.
Foucault, Thierry, and Sophie Moinas. “Is Trading in Dark Pools Self-Defeating?” The Review of Financial Studies, vol. 26, no. 6, 2013, pp. 1435-1484.
European Securities and Markets Authority. “MiFID II and MiFIR.” ESMA, 2017.
ICMA. “MiFID II implementation ▴ the Systematic Internaliser regime.” International Capital Market Association, 2017.
Consob. “The impact of MiFID II on the European equity market structure.” Quaderni di Finanza, No. 84, 2020.
CFA Institute. “Market Microstructure ▴ The Practitioner’s Guide.” CFA Institute Research Foundation, 2021.
O’Hara, Maureen. Market Microstructure Theory. Blackwell Publishers, 1995.
Harris, Larry. Trading and Exchanges ▴ Market Microstructure for Practitioners. Oxford University Press, 2003.

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Reflection

The integration of Systematic Internalisers has fundamentally reconfigured the architecture of market access. The mandate for best execution now requires a level of systemic sophistication that transcends simple price-seeking. It demands the construction of an intelligent operational framework, one that perceives the market not as a single pool of liquidity, but as a distributed network of interconnected venues, each with unique properties and protocols. The data and strategies presented here provide components for such a framework.

The ultimate question for any trading principal is how these components are assembled within their own architecture. How is your firm’s system calibrated to dynamically source liquidity, measure its own performance, and adapt to a regulatory landscape that is in perpetual motion? The quality of that system directly translates into the quality of your execution.