How has client demand for FX algo trade analytics evolved in recent years? What are the key drivers behind this?
Over five years ago, post-trade analytics for FX algos was the industry standard for TCA and was sufficient at that time to meet client demand. However, as the regulatory landscape has been transformed by best execution obligation requirements under MiFID II, we have witnessed a similar evolution in client needs in the FX algo TCA space. The new requirement to create best execution frameworks fostered a dialogue on how to define and optimise performance benchmarks. This dialogue led us to expand beyond standard price benchmarks that took a static snapshot in time, such as slippage versus arrival or risk transfer price, and incorporate quality of fill benchmarks, such as passive fill rates.
In addition to measuring fill quality, clients were keen to measure market impact and took an earnest look at post-trade mark outs – anywhere from one second to one hour after execution. In order to first minimise and then predict market impact, this naturally led to the examination of pre-trade analytics and the development of FX algo trade cost models. Today, we’re now seeing a growing need for real-time analytics, as clients seek dynamic transparency and more informed in-flight control.
How does UBS ensure that the analytics tools on offer to support algo clients meets these needs?
In response to increased client demand for real-time TCA, we recently launched a real-time algo analytics tool on UBS Neo, our platform that connects clients digitally to the best of UBS. Our new intra-trade TCA rounds out our pre-trade and post-trade algo analytics suite and provides our clients with execution insights throughout the life of their order.
With real-time performance feedback, clients have better tools to navigate shifting market conditions and to quickly adjust their algo implementation strategy to excel in the current environment. In-flight analytics inform traders if algo strategies need to be switched in-flight and gives our clients increased control and improvement of trading outcomes. Moreover, real-time analytics also empowers our own FX algo sales trading teams to enhance the advisory service that they provide clients in terms of algo selection and strategy implementation.
What are the key features of the UBS analytics offering? How do you use these to help clients to achieve their execution goals?
Our new in-flight analytics give clients increased visibility of how and where their algo orders are executing against relevant benchmarks, and also helps to guide and optimise trading decisions. After beta testing the product over the past couple of months, we’ve been able to glean valuable feedback to further optimise the catalogue of data, overall GUI experience and data visualisations. While we’ve enriched the charting and graphics, we’ve also simplified the number of clicks needed to navigate the tool. We’re excited to imminently release our enhanced real-time TCA product, which is a telescope into current market dynamics and also compares pre-trade estimations, intra-trade executions, and post-trade performance with rich, customisable charting and graphics.
What does this new development mean for the evolution of the UBS algo offering going forward?
As real-time trade cost analytics lead to heightened in-flight awareness of algo performance, as well as overall richer datasets around such performance, this will lead to more critical thinking and conversations around how to further improve and innovate today’s algo solutions. While post-trade TCA was instrumental to driving the first wave of enhancements to our algo suite, the incremental insights from real-time TCA will empower UBS and our clients to further optimise our FX algos solutions.
Moreover, we believe that real-time insights will lead to (1) a deeper knowledge of how different algo strategies react to and perform in various market environments, and therefore (2) an increased switching between algo strategies to navigate market shifts. As a result, we think we’ll see a growing demand for custom algos that combine different algo strategies and allow clients to transition from one strategy to another based on various market conditions.
In fact, UBS already has an advanced and differentiated custom algo framework in cash equities and futures and it is these asset classes that oftentimes take the lead on electronic execution innovation and technology developments. In those asset classes, we’ve built a highly flexible custom algo framework which allows clients to configure between different measures of UBS algorithms based on the measures of time, price, performance, cost, spread, volumes and/or order characteristics. These measures are evaluated in real time and throughout the life of the order.
Our custom algo framework has enabled our clients to intelligently and automatically navigate the ever-changing liquidity landscapes in cash equities and futures and the continuously shifting liquidity regime in FX is no exception. As real-time TCA drives more awareness around which algos perform best during various market conditions, we anticipate a growing client demand for tools that allow them to pivot between say, passive and opportunistic strategies based on real-time factors. As this client demand grows, we’re excited to bring that innovation to the FX algo space to create bespoke solutions and to deliver the strength of UBS’s overall electronic trading franchise to our FX algo clients.
