TradeTech FX Daily 2022 | Page 27

THETRADETECHFX DAILY from the floor

The everevolving landscape of the trading desk

The TRADE speaks to GORDON NOONAN , head of FX and rates trading at Schroders , about ways to future proof trading desks , the opportunities DLT can provide and how execution styles can be adjusted to improve liquidity targeting .
How can technology stacks , operational processes and trader skills be adapted to help future proof trading desks ? As trading technology further advances along with the increase in availability of datasets , it has become even more essential for trading desks to leverage these capabilities to improve execution decisions , maximise efficiency and reduce risks . Traders will need to be able to develop skills that will allow us to use these tools to solve for trading challenges . This can range from improving programming skills ( python , SQL , etc .) data visualisation ( Tableau / Power BI ) and understanding electronic communication protocols ( FIX connectivity , FDC3 ). In the future , there will be an increased focus on the use of data science to improve performance in our industry .
What opportunities do you think DLT can provide to enhance trading and settlement efficiencies ? DLT has the potential to significantly enhance trading and settlement capabilities , removing friction and asynchronous data from the current ecosystem . We should see a reduction in numerous participants maintaining individual datasets across disconnected platforms , eliminating the need for reconciliation . Self-executing smart contracts embedded in assets could perform servicing functions such as settlement , confirmation and payments . We are monitoring developments related to atomic settlement , or near-simultaneous settlement , and think the upcoming moves of markets to T + 1 will highlight key challenges to be explored . These include the protocols on how different DLT networks connect with each other , the regulation governing trading and settlement of DLT assets and the liquidity profile of these assets .
How can execution styles be adjusted to access efficient liquidity in high volatility environments ? The key skill set of a trader is to adapt their execution style to changes in the liquidity and volatility regime with a view to obtaining best outcomes for clients . It is important for us to understand which strategies work best in each liquidity regime and react accordingly . The key for us is having systems available that signal regime changes , allowing us to switch to proposed strategies on demand without the need for excessive manual intervention . We continue to partner with our EMS partners and bank counterparts to improve capabilities on trading platforms and algorithms to achieve this .
Do you see a shift to more multi-asset trading hubs ? What more needs to be done to facilitate this ?
We are certainly seeing a trend develop over recent years of desks moving to a more multi-asset trading model . Asset class experts will continue to be a vital part of any trading desk but there is certainly room for multi-asset traders who can move seamlessly between asset classes as required . To achieve this , more commonalities should be found across asset classes so that the technology and processes can be streamlined and increase scalability . This allows for more capacity to focus on the more niche areas in each asset class that cannot be normalised .
With respect to data and electronic execution capabilities , which FX products need the greatest focus and improvement ? On the data front , the swaps market continues to remain opaque with forward pricing not as visible as the spot market . Pricing across banks vary materially in the swap space . While the majority of FX products are tradable in the electronic space , work still needs to be done on communicating market order types and limit price restrictions , protocols widely available in the equity space . Option pricing is the one area where we need to see movements in the electronic space as it is still a manual execution process for many market participants .
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