Evolution and Intelligent Design – a match made in MiFID

By Nico Christodoulides | 15 August 2017

The Quality of Execution provisions of MiFID II apply pressure on both the buy-side and sell-side to provide self-assessment of their execution capacity. Critically, investment firms will be required to answer hard questions about their allocation of trades between markets and brokers. These questions require a formal response. While it is tempting to settle for an off-the-shelf package, a rigid solution that does not link to the firm’s operations has costly drawbacks.

In the MiFID world, intermediaries will independently evaluate investment firms’ trade allocation policies. This introduces competitive pressure, where in addition to demonstrating compliance to the conduct authority, firms will have to defend their policy to gatekeepers in the market. This requires a data-driven approach in which the soundness of the allocation decision can be systematically demonstrated.

System design plays a critical role, blending two seemingly inconsistent design features:

a) Forethought The system should be configured upfront to capture a reasonable range of quality metrics. Congruent live interfaces and reporting should be put in place.

b) Adaptability The design should allow for dynamic changes to the quality model, in response to salient changes in the environment (e.g. trade in new lines of customised instruments, the closure of alternative exchanges, and the industry acceptance of new impact models).

Quality of execution design guidelines should include the following:

a) Modularity Rather than opt for a single black box, the firm should implement coupled modules, each of which can be redesigned or reconfigured in response to environmental change. This reduces the overall cost of ownership (as small changes do not require wholesale system overhaul) and minimises the downtime associated with system change.

b) Integration In general, systems should be preferred that link directly to the firm’s core decision-making systems – from portfolio modelling through to settlement. This approach allows live changes in order routing, in response to a broad set of relevant market signals. This obviates risks associated with manual transfer to a decoupled quality-of-execution system.

c) Reporting The MiFID context requires after-the-fact explanations of why execution decisions were taken. This calls for automated reporting of every aspect of the quality assessment process. Instead of relying on a dedicated (or manual) reporting system, the execution assessment modules should generate customisable reports, explaining the decision behind order routing, supplemented with relevant contextual information.

d) Dynamic Modelling While index-based and transaction-cost-analysis approaches dominate, there is no consensus on what a best-practice quality of execution model looks like. This leads to a variety of approaches, exacerbated by MiFID’s requirement that firms move away from the focus on price, to inclusion of such factors as speed and probability of execution. This favours implementations that are able to accommodate more than one quality model, and where the range of models changes over time. Shrink-wrapped solutions wedded to a specific set of models risk trapping the user with out-of-favour quality assessment metrics.

e) Segmentation MiFID provides for disaggregated disclosure by exchanges. This accommodates the fact that execution efficiency for a single trading facility will vary across categories of instrument and trade sizes. This variance changes over time for the same facility. Accordingly the order routing system should rank exchanges by a set of market-related factors, and provide dynamic ranking based on live orders. This would take into account the instrument types and order sizes in the implicated transactions.

f) Versioning Information systems allow routing revisions of data. Since the motivation for quality of execution disclosure is to provide reasons for order routing after the fact, unrevised data that pertained at the time of decision should be available without time consuming and error-prone reconstruction. Accordingly, the system should maintain versions of the histories of the client segmentation, and exchange rating data before and after all revisions.

g) Openness: It is important to evaluate trading facilities with which the firm has not dealt in the past. Failure to do so risks sub-optimal routing, as these neglected exchanges may offer better execution under some circumstances. This requires importing the MiFID-mandated disclosures from exchanges, along with third-party research that the firm is able to acquire. This data should be fully integrated into the order routing algorithm.

The ESMA guidelines leave enough leeway for investment firms to adopt an own approach, customised to their operating conditions. Investment firms can derive value by rising above the statutory minimum reporting requirement. Having implemented the design features listed above, care should be taken to maintain quality models that reflect developments in theory, changes to the firm’s business mix, and the emergence of new trading facilities. New data sources should be coupled. The versioning and openness guidelines allow firms to supplement their reporting with scenario analysis, improving the calibre of future routing.

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