Charles Ellis, a trader and quantitative strategist at Mediolanum Asset Management, explains how data can be used to help generate alpha signals.
The first thing that Ellis points out is how trading firms can most effectively use data is dependent on their investment process and the type of research questions they are trying to use the data to answer.
For starters, he says, firms need to consider what investment time frame they are working towards.
“Then you have to ask which of these time frames can we add the most value to? What data do we have access to? And then it goes into what sort of questions can we answer using this data over these time frames?” comments Ellis.
The increasing use of AI technology is likely to create incumbent firms that dominate markets, said panellists at the Profit & Loss Forex Network New York conference. However, they also said it might not be the biggest firms in the markets today that become these incumbents.
“I think [AI] is changing the landscape quite a bit,” said Andrej Rusakov, a partner at Data Capital Management, a hedge fund that uses AI tools to develop trading strategies. “People who are missing the wave are going to be left behind, I don’t think there’s any question about it. I think that human day traders will be wiped out, if they’re not already.”
Rather than moving in a synchronised manner, speakers at the Profit & Loss Forex Network Chicago conference predicted that emerging market (EM) performance has become divergent due to idiosyncratic factors within each country.
“In general, EM does well when you have at least two out of three things: one is global growth, two is a weak dollar, and three is lower US rates. So, if you look at this combination and where we are in the cycle, especially given all the easy money that we’ve had since 2008, I would be very careful with the emerging markets right now,” said Mo Grimeh, CIO at Mogador Capital Management at Profit & Loss Forex Network Chicago.