Buy-side traders risk redundancy and irrelevance if they do not adapt to the opportunities for automation of fixed-income execution provided by new technologies, delegates were told in the FILS panel session on the use of artificial intelligence and machine learning (AI/ML).
“Traders need to embrace those changes or go find another job. The path to AI-driven investment is happening,” said Carl James, global head of fixed income trading at Pictet Asset Management.
According to James, Pictet’s trading desk is working increasingly closely with the firm’s portfolio managers, due to their growing ability to automate smaller trades and spend more time on data analysis. Specifically, traders are more frequently offering PMs opportunities to take on risk into their portfolios, based on combining the firm’s own trading data with third-party information services to derive new insights.
“As a buy-side dealer you can be passive, waiting for the order to come in. But you can also be proactive in understanding the PMs’ strategy. Using data will help traders add value,” he said.
Stuart Campbell, head of trading at BlueBay Asset Management, acknowledged that the firm had recently wound down headcount on its low-touch trading desk, due to the increased ability to automate smaller trades. However, Campbell attributed the vast majority of progress in trade automation to use of rules-based systems, rather than AI/ML.
“But it won’t be that long before we have robots recommending we go out to three brokers rather than five for a particular trade, and identifying those brokers for us,” he said.
Campbell’s assertion on the use of rules-based automation in fixed-income trading was supported by an audience poll. Asked if they were already using auto execution, 34% delegates said that they were, while 44% said they were looking at topic.
Both trading heads acknowledged that the pace of technology change required them to evolve the skills available on their fixed-income desks. BlueBay’s Campbell said that his traders needed to reskill and retool to continue to be effective in the medium term.
“Our high-touch traders are very experienced. The challenge is to get them to evolve and use the technology is available to them,” he said. “That’s not easy when you’re getting long in the tooth.”
At Pictet, James said that the firm was already hiring new staff with more data-handling than trading experience, with existing traders also being asked to develop programming skills, in order to work closely with the firm’s data scientists on new technology use cases. He added that portfolio managers also had to adjust to working in a more data-driven environment, noting a higher degree of quant-based skills in Pictet’s PM team.
Campbell agreed that coding and data experience was becoming more important in the recruitment process, as well as other non-trading skills.
“My job has changed dramatically over the last few years. I now have to understand how we can use hosted services as that’s now part of the overall equation.”
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