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the people presenting that data , it is not going to be as valuable . In the same breath , it has to be understood that the role of the trader is still paramount .
“ Once people realise that you can ' t exclusively do this from a data science view , you need to pair it with someone who is living and breathing in this environment , that ' s when you start to really get some of these experiments that are successful , where you actually start to see cost savings or optimised trading ,” argues Erin Stanton , global head of portfolio and trading analytic client support at Virtu Financial .
“ We ’ re starting to think about how we can summarise down the metrics to two or three really easy to consume pieces of information and present those to the trader as a co-pilot scenario . It ' s not autopilot - I ' m not bypassing the trader - I ' m
“ The more regulated the market and the more exchange driven it is , the more effective I believe the TCA can be .”
MARK MONTGOMERY , HEAD OF STRATEGY AND BUSINESS DEVELOPMENT AT BIG XYT information , what they can do is they can find what those post-trade insights are ,” says Bryan .
“ By putting it into some sort of pre-trade philosophy or mechanism , you ' re able to test if those actionable insights were valuable and then that gives you more data to support getting closer and closer to the best results over time .”
Collaboration is key Increased collaboration between traders and data scientists is proving beneficial in helping improve future execution strategies . It is worth noting , however , that a huge level of trust needs to exist between the two .
Collaboration needs to be impartial . If traders don ’ t have the confidence in the underlying data , or instead enabling the trader with better information than they had previously .”
Collaboration is essential , however , trader intuition is still incredibly important given the varying nature of financial markets on a daily basis .
“ The trading research team can do much better analysis on smaller orders , partly because liquidity profiles are easier to understand and are more predictable . As soon as you get an order that ' s more than about 30 % of average daily volume – i . e .
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