Score Priority renews deal with RCM-X for equity algo execution

Rick Steves

The partnership will provide Score Priority’s new and existing institutional customers with access to products specifically designed with market microstructure nuances in mind. RCM-X’s algorithms use a data-driven approach for continued improvement and development.

Score Priority has extended its existing partnership with RCM-X, a provider of algorithmic execution strategies and quantitative trading products for institutional clients.

The partnership will provide Score Priority’s new and existing institutional customers with access to products specifically designed with market microstructure nuances in mind. RCM-X’s equity execution algos use a data-driven approach for continued improvement and development.

Score Priority CEO Tony Huck, said: “Low volume or high volume, tail event or tame environment, it doesn’t matter — the importance of negating order impact in markets and the efficient use of traders’ time remain paramount to firms’ P&L. Our ongoing relationship with RCM-X allows our customers to have a flexible equity execution algo toolbox that can be tailored to bespoke needs via RCM’s Strategy Studio.”

Joe Signorelli, Chief Executive Officer at RCM-X, added: “Under Tony’s leadership, and supported by RCM-X management, we are taking our equity execution algo service to the next level. Score Priority’s Ferrari-like technology alongside our algo suite gives clients access to our execution technology.”

Score Priority has doubled the size of its team over the course of the past year. The firm, an SEC-registered broker-dealer, member of FINRA/SIPC, intends to provide customers with RCM-X’s equity execution algo integrations via the Lime platform. Institutional customers will be able to find the liquidity and execution they need in the manner that best suits their strategies.

A number of firms within the financial services industry have launched algo execution products. Last year, Virtu Financial introduced expanded its global TCA offering with the launch of a new analytics product dedicated to FX algorithmic execution. The new addition to Virtu’s FX TCA offering merges data from three distinct sources:

FX benchmark data sourced from Virtu’s market-making business;
Virtu’s global, broker-neutral market impact model: FX Agency Cost Estimator (ACE);
Direct connections to bank algo providers on behalf of clients that subscribe to the offering.

Earlier this year, Pragma launched deep-learning-enabled execution algorithms. THe project started in 2018 as the firm explored if deep neural networks could be applied to an execution algorithm’s micro-trading engine– governing decisions such as the routing, sizing, pricing, and timing of orders – and deal with complex multi-dimensional trading challenges more effectively.

Following a beta launch in 2020, Pragma managed a number of controlled trials with its clients. It observed a significant improvement to execution quality, with an average shortfall improvement of 33% to 50% across billions of traded shares.

FX execution algorithms have severe regulatory implications, said BIS

Although it is established that Execution algorithms (EAs) have contributed positively to FX market functioning, they also give rise to new challenges for regulatory bodies, the Bank for International Settlements stated.

Execution algorithms have seen a rise in usage amid an increasingly decentralized and fragmented trading environment. This has helped support price discovery and market functioning but also has the potential to create new risks, says the BIS report.Prepared by a study group led by Andréa M Maechler, a member of the Governing Board of the Swiss National Bank, the report draws on a survey of 70 sophisticated market participants globally and extensive industry-wide outreach.

It concludes that while EAs improve market functioning, they also: transfer execution risk from dealers to end-users; contribute to changing liquidity dynamics and the underlying market structure; and raise the bar for market participants in accessing the data, skills, and tools required to navigate this market successfully.

EAs may also create self-reinforcing loops and exacerbate sharp price moves, although initial observations from the Covid-19 pandemic suggest that these risks may be less acute than expected.

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