Optimizing Trading Workflows With Agile Platforms
Buy-side trading desks have unique requirements, but all need to future-proof their platforms.
Should buy-side trading desks buy technology or build their own? How are institutional traders extracting maximum value from data? What is the potential — and what are the limitations — of automated trading?
Those were a few of the questions explored in a recent buy-side roundtable hosted by TradingScreen in New York.
On the buy-versus-build question, roundtable participants noted that every trading desk has its own unique workflow and its own unique needs for solutions, so every desk has its own unique answer. This differs from bank broker-dealers, where the universe is much smaller the suite of trading products and services is comparatively standardized.
“Unlike the sell-side, most buy-side firm have unique workflows, which require them to tailor technology and data solutions to drive performance and meet ever-growing regulatory mandates,” said Nasdaq Head of North American Equities Tal Cohen, who moderated the roundtable.
Mostly, buy-side trading desks buy systems ‘off the shelf’ and customize to their own specifications — so, some buying, and some building. But today’s increasingly complex market calls for more sophisticated, higher-horsepower products, so there is a discernible shift towards buying.
“We’ve gone from mostly proprietary technology to mostly third-party,” said Enrico Cacciatore, Senior Quantitative Trader and Head of Market Structure & Trading Analytics at Voya Investment Management.
“We had to have the skill-set to maintain it, and our corporate model is to scale and simplify. So we asked ourselves: ‘Can’t we build this in a third-party product and maintain our edge?’”
For a large investment firm that trades different asset classes, with different trading protocols, multiple ‘best-of-breed’ solutions are required for specific areas of the trade lifecycle. Then the real challenge is stitching it all together so that systems are interoperable with each other and also the internal technology.
“We count on third parties but it’s also critical to have an internal team of developers to handle integration with multiple platforms,” said Alessandro Barroso, IT Manager, Investment & Wealth Management Technology at Franklin Templeton.
The largest buy-side institutions with trading desks across continents face another challenge: maintaining standardized workflows while giving individual trading desks some leeway. For example if Sydney traders have a way to efficiently trade Australian securities that differs from how they do it in London, that should be accommodated.
“The utopian view is that it’s all going to be consistent,” said Eric Thorson, Senior Delivery Manager for Portfolio Management Systems at Vanguard. “But it never really is.”
Or as another roundtable participant said, it’s about “balancing between effective change management and still allowing for the ‘secret sauce’.”
One shared pain point for institutional managers is data management. The problem isn’t a lack of data; on the contrary, the challenge is sifting through massive amounts of data, finding what’s usable, and acting on it before its usefulness expires.
“There is too much data, and most of it is bad,” said Jose Marques, CEO of Inferent Capital. “How do we make data useful in a timescale that’s relevant to the problem we’re trying to solve? Post-trade is fine, but that’s not going to add alpha.”
Roundtable participants were in consensus that almost every buy-side firm is working to optimize data management; however these is a long way to go, which presents an opportunity for technology vendors to step in with the right solution.
Institutions are either developing or shopping for more robust data-capture models, which will be overlaid by more advanced functionality such as aggregation, pattern recognition, and visualization.
One roundtable participant noted his firm is at the beginning phase of leveraging data to improve trading decisions. “We are not there yet,” this participant said. “We are collecting data and we have a data scientist looking at it. The question is, how is it going to add value to our process?”
“The question to ask is not what the buy side needs, but what will the buy side need,” TradingScreen Senior Developer Edmund Caraceni told Markets Media after the roundtable.
“For a technology provider, having a future-proof lens enables readiness for shifts driven by regulatory demands for the data aggregation and business-intelligence tools that enable best execution across asset classes.”
Regarding the trading desktop of the future, one buy-side technologist who participated on the roundtable noted a secular shift away from a closed system, and towards a more open model that can be described as a container with multiple specialist fintech tools.
Machine-based trading will continue to gain traction, especially for what one roundtable participant described as “low-risk, low-value trades.”
Trading desks “need humans — we’re the pilots of the airplane,” another participant said. “We can put things on autopilot, but we need humans. Technology is there to scale the stuff we don’t need to deal with.”
The mix may change over time, but trading will always be man plus machine, not just one or the other.
“Humans create technology to extract away all the tedious things that humans are good at the first 10 times, but then they’re terrible at,” said one participant. “Technology can run with that, and when something’s not going well, it gives the human the context they need to engage. That paradigm works.”