Page 13


Data Science And The Trading Desk By Terry Flanagan, Managing Editor, Markets Media

Francis Bacon, René Descartes and Isaac Newton were among pioneers who advanced the idea of making conclusions based on observation and evidence, rather than just reasoning.

Sell-side trading desks utilizing data isn’t new. What is new is the level of sophistication of buy-side investment managers, who need to see evidence that a methodology works. Brokers need to show, not just tell.

Centuries later, institutional brokers are incorporating tenets of the scientific method into their own pursuits of buying and selling blocks of equity.

“Our clients are becoming increasingly sophisticated in how they measure results and are pushing us harder to optimize our capabilities to solve their specific use cases,” Lopez said. “They require empirical evidence that taking a particular approach will result in lower implementation costs of trading.”

The nutshell premise is that data and proof walk, conjecture talks. This is especially the case in a rapidly evolving market with a multitude of promising — but untested — trading options. “At UBS in the Americas our view is that the equity ecosystem continues to evolve and become increasingly complex in terms of new order types, new venues and new sources of liquidity,” said Todd Lopez, Head of Americas Cash Equities at investment bank UBS. “There continues to be more competition and diversity in liquidity sources. To effectively navigate this environment we need to understand in forensic detail when and how to access these sources and leverage new order types.”

‘Significant Differentiator’ “A broker’s client base is diverse and each buy-side customer may have varying order flow and therefore different liquidity needs,” said Curt Engler, Head of Equity Trading, Americas, at J.P. Morgan Asset Management. “The ability to test varying theories and quantify the results, especially client- specific needs, should be a significant differentiator for algorithmic providers.” In the early 17th century, Galileo Galilei used the scientific method to contradict the long-accepted

Q4 • 2018 | GLOBALTRADING Global Trading Q4, 2018 Issue #68  

Fixed Income TCA: A Competitive Differentiator Global Trading Q4, 2018 Issue #68  

Fixed Income TCA: A Competitive Differentiator