5 min read

Best Execution And The “Electronification” Of High Touch Trading

Best Execution And The “Electronification” Of High Touch Trading

By Michael Mollemans, Head of Sales Trading Asia-Pacific, Pavilion Global Markets

Best execution is an evolving process, and so it is incumbent upon us to anticipate the trend in service expectations.  

michael-mollemans-pictureThe unbundling of research brought about by the Markets in Financial Instruments Directive (MiFID II) put the cost of execution into the limelight with many buy-side traders responding by increasing their use of low cost, “low touch” algos. Best execution policy disclosures also brought quantitative performance and qualitative service factors into focus. As best execution regulation and service expectations evolve, so too do the traditional “low touch” and “high touch” roles, with the road ahead leading to an electronification of “high touch” client service partnerships. 

Liquidity issues in certain names, and on certain days, are always a source of frustration for buy-side traders. Markets are dynamic and liquidity in small- and mid-cap names can be here today, gone tomorrow, and a few illiquid names in a “basket” or “program” can destroy overall performance numbers. A sales trader’s ability to combine expert advice on liquidity-seeking algorithm (algo) parameter settings with a breadth of counterparty relationships gained through experience makes all the difference when aiming to achieve the highest possible ranking in a client’s execution performance scorecard. Buy-side traders are increasingly taking a multi-factor approach when evaluating brokers against their peers, with value-added service and other qualitative measures weighted highly next to execution quality. A “high touch” approach, in an otherwise “low touch” algo business, not only helps achieve a superior weighted average performance result, but also helps move up in the performance scorecard ranks. 

Block crosses can help enhance trading performance but can also damage client trust if crosses are sourced without consent, or if the client’s unique qualitative parameters and constraints are not properly followed. Sales traders certainly need to interact with electronic crossing venues selectively while seeking to utilise the breadth of counterparty relationships. When crossing stock at a price, however, there is no substitute for skilled technical analysis of stock trends to estimate the periodicity of alpha so as to minimise the chance that stock prices trend into you only after executing your block at a relatively unfavourable price. Timing contribution of executing a block at a price, and the opportunity cost of not executing a block, must be carefully considered. Information leakage costs must also be considered when reaching out to counterparty relationships. Block executions provide an opportunity to minimise impact but if unnecessary information leakage is created they can also hurt overall performance. Automated “smart IOI” (Indications of Interest) processes, geared to targeting known holders of a name, can be very helpful when trying to minimise leakage. 

Reliability of execution across a robust trading platform that can sustain any type of system failure is often cited by the buy-side as a key qualitative factor when it comes to making broker routing decisions. Availability of backup algo networks is valued because the last thing clients want to hear an hour into the trading session is “trade away please.” Market data issues, network outages, database failures, algo engine issues, etc. can happen, but the ability to fail over to a parallel backup algo infrastructure makes all the difference when it comes to providing reliability of execution. A sales trader’s ability to provide clients with quick and detailed communication about the nature of a system failure, and an informed estimate on when systems will return to normal, is always appreciated.  

The trade lifecycle doesn’t end at execution, it ends at settlement. Smooth settlement, especially with difficult emerging market ID matching requirements and amended settlement terms, requires constant communication between traders and settlements teams, which can be a challenge if these teams are separated in different buildings or cities. Trading and settlements teams also need to rely on experience to help anticipate issues and become problem solvers, when needed, to assure clients get a consistently reliable settlement experience. 

Analytics are at the front-and-centre of the trading relationship as buy-side traders aim to maximise alpha through smarter execution strategies. Sell-side traders are expected to have deeper discussions with clients around transaction cost analytics (TCA) and so data visualisation tools are being used more and more to assist communication with clients across a growing number of data points. TCA based primarily on performance measurements versus “VWAP” or “arrival” benchmarks can be misleading when best execution regulation requires the consideration of both quantitative and qualitative factors across the entire trade lifecycle. MiFID II regulation and the regulatory technical standard (RTS 28) requires Best Execution Policy annual reports to be disclosed publicly for the first time ahead of the April 30th 2018 deadline. However, regulators have made it clear that next year, and in the years to follow, best execution policy reports are expected to become increasingly specific and transparent about how venue and counterparty routing decisions are made.  

Pre-trade reports set strategy selection in motion. Then, real-time market data feed into technical trend analytics designed to help sales traders add alpha by capitalising on directional opportunities with the help of adjusted algo parameters and curve tilts. Real-time analytics are designed to be actionable but their value is largely determined by a sales trader’s ability to interpret the signals and take action on opportunities in spread capture, timing contribution, opportunity cost, etc.  

Venue analysis is a great tool to drive informed discussions with buy-side traders around performance at the venue level and help the sell-side to act in the best interest of clients by removing hard-coded venue biases. Venue analysis also sheds light on the venues that provide the most opportunity for earning spread capture and speed of execution, with the lowest reversion cost. Guided conversations with clients about venue performance provides added depth of understanding of their performance goals, which can help sales traders fine-tune dynamic venue prioritisation and smart order routing strategies across various market conditions and levels of trade urgency.  

Monitoring and reviewing of execution quality requires constant communication between buy-side and sell-side traders and yields a valuable feedback loop used to help produce performance results with improvements to algo parameter settings and customised client service partnerships. Distribution of weighted average trading performance is increasingly being looked at by the buy-side, and tightening of the distribution of performance is becoming a goal in itself. Clearly, from a risk point of view, buy-side traders don’t want long-tail, “all over the map,” performance outcomes.  

To be successful at delivering consistently above average, low standard deviation, trading performance to clients, sales traders need to bring automated “low touch” tools and “high touch” market experience together when navigating through the latest market-moving news announcements, sentiment changes and directional trend shifts. Algo engines are often being equipped with news factor data but they cannot yet compare with an experienced trader’s ability to take news on complex economic and geopolitical events and translate it into alpha producing opportunities for clients.    

Transparency is often cited by the buy-side as one of the main qualitative factors considered when making broker routing decisions. Transparency of order routing logic and smart order routing prioritisation settings require informed communication between buy-side and sell-side traders. Email blasts with technical update jargon and marketing brochures offering limited detail are not enough. Sales traders are expected to help clients understand what is happening, or changing, “under the hood” by thoughtfully and efficiently translating the proprietary technical language. The overall goal is to help clients choose the best algo parameter settings and smart order router preferences to get the best possible performance result.  

Execution consultancy services are needed more than ever as the range of algo strategies, alternative venues, and smart order routing preferencing options widen. Sales traders are expected to assess new technologies, like artificial intelligence or machine learning, and advise clients on where quantifiable, statistically significant, results are being seen, or to what extent it is just marketing. Sales traders are expected to stay updated on market structure changes and advise clients on how to best position themselves to take advantage of change.  

All in all, the sell-side service model that is best positioned for the anticipated change in best execution regulation and service expectations is one that brings the key components of “low touch” and “high touch” roles together seamlessly into one combined approach, which is the aim of the Pavilion Global Markets value proposition. Algos and automated processes do not produce best execution by themselves; rather, they are tools and efficiencies that allow sales traders to allocate more time to the qualitative value-added side of trading services. Access to liquidity is a primary concern and so sell-side traders are expected to regularly assess all new and alternative electronic venues. At the same time, they must source liquidity from a myriad of counterparty relationships gained through experience. Constant monitoring, review, and communication with clients around pre-trade, real-time and post-trade analytics will not only support efforts to produce superior weighted average performance results, but will also help tighten the standard deviation of performance outcomes over time.

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