10.03.2014

The Bionic Trading Desk

10.03.2014
Terry Flanagan

Today’s ultra-fast markets are demand platforms capable of real-time decision support and intelligent analytics. The trading desk that can most efficiently analyze ever-growing volumes of data and uncover ever-fleeting opportunities for alpha across asset classes and across the globe will have a significant advantage.

“The issue is how to make a better trading decision in a fast paced environment,” said John Adam, global head of product management at trading systems provider Portware. “What new and interesting ways do I have for looking at the trade and the data, and how do I integrate all this with the rest of my critical functions? So that’s the theory.”

Putting the theory to practice, the tools that are most relevant are predictive analytics, transaction cost analysis and data visualization. “Those are really the three areas where I’m seeing the most innovation in equity trading desks,” Adam said.

Trading desks have an opportunity to gain a competitive edge by integrating these three technologies.

“The next step, in a word, is integration,” Adam said. “These functions have less value when they exist separately and they have an exponential value when they’re combined. Everybody has commission schedules, data visualization and research targets and predictive analytics.”

Used in combination, TCA, predictive analytics and data visualization enable traders to “get a real-time read of which broker is going to give me the best performance on this trade in real-time based on a particular set of market conditions,” Adam said.

TCA systems are moving toward real-time and predictive TCA, noted Adam. Ten years ago, a desk would run a monthly report on broker commissions and broker performance relative to a benchmark.

“Now before I even send the order out, I’m selecting my algorithms and my broker based on a pre-trade analysis of who’s going to handle this order the best,” he said, “As market conditions change, I might switch strategies, I might hop from one algorithm to the next because the market is moving faster and the decision I made an hour ago might not be right for where the market is or how it’s behaving now for a given stock.”

A very common decision for head traders is determining which brokers to send an order to based on commission budgets.

“If I have two brokers that I’m targeting to pay an equal amount of money for the quarter, which one is going to give me better performance on the algorithm I want to use?” Adam said. “Let’s start to look at optimizing the algorithms based on my research commission targets for a particular broker. Rather than have that information in a spreadsheet, I want to have it directly accessible and guiding my decision in the EMS.”

Data visualization also needs to be tightly integrated and seamlessly accessible to the trading desk. “If there’s a chart or a heat map that indicates possible performance scenarios, I want to be able to interact with my order directly through that chart,” Adam said. “I don’t want to generate the chart, swivel in my chair, look at it, swivel in my chair again, go back to my blotter and trade it there. That should all be integrated for me.”

Featured image via Maksym Yemelyanov/Dollar Photo Club

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