The widespread use of algorithmic trading has lessened the need for interaction between the buyside and sellside, and brought with it increased reliability, faster speeds and lower costs. However, it also brings technology-related risks and a lack of transparency.
It used to be that equity trading was a telephone-based activity where the traditional buyside trader will be talking to somebody at the other end of the line, who will then be talking to the sellside trader from the brokerage house. The sellside trader would then work the order in the market usually via an algorithm.
Nowadays, with the advent of technology, this two-step process has almost disappeared as the buyside traders now have access to all the algorithms from the different brokerage houses, allowing them to work the orders directly into the market themselves.
The widespread use of algorithmic trading – basically the process of using computers programmed to follow a defined set of instructions for placing a trade – means that it is no longer necessary for the buyside traders to speak to their counterparts every time they make a trade. However, they still do so when sourcing large blocks of shares or trying to move huge amounts of cash into the market.
Different asset management houses have responded in their own ways to this changing development in equity trading. In the case of J.P. Morgan Asset Management, their equity trading model involves segregating their flows on a liquidity basis using algorithms.
They have also deployed a team of specialist traders who deal with stocks that are more difficult to trade. These so-called “active” traders also use a combination of algorithms and telephone calls to source liquidity for the stocks they’re trading.
Algorithmic trading definitely has its merits. Principally, increased reliability, faster speed and lower costs. On the flipside, algorithmic trading is also known for its lack of transparency, and has been a source of technology-related risks such as flash crashes.
For Lee Bray, head of equity trading for Asia-Pacific at J.P Morgan Asset Management, algorithmic trading has enabled buyside institutions and asset managers like J.P. Morgan to have a much better understanding of how they’re implementing their clients’ businesses when it comes to equity trading. Bray’s team is separate and independent from the equity trading desk of J.P. Morgan Investment Bank.
“That has led to better execution in terms of decision-making. Personally, I think it’s been good progress. We have more tools now to access the market and measure what we’re doing in terms of implementation,” says Bray.
J.P. Morgan Asset Management was one of the early adopters of algorithmic trading and machine learning for equity trading. Bray, who became head of the firm’s equity trading desk in 2013, previously worked on the equity trading desk in London for 13 years before coming to Asia.
“One of my first remits when I first came over here was to globalize the regional equity trading desk. At that time we were globalizing our operations across the board. One of my remits was to globalize the Asian function from a trading perspective and bring it in line with what’s happening in the US and Europe in terms of the workflow process and how we’re approaching the brokers in the street. It is all aligned now after four and a half years,” says Bray.
It took about two years for the efforts to come to fruition, but upon completion Bray believes J.P. Morgan’s equity trading capabilities are now ahead of its peers.
“When I first started in the business 20 years ago, there was far less integration between equity trading and the technology aspect. Now we have six to seven people from IT sitting directly on the trading desk. So you can imagine that the interaction between the trading desk and technology is a lot more symbiotic now than it has been previously,” says Bray.
The big difference in equity trading in recent years is that the toolsets that are available to buyside traders have converged with what’s available to sellside trading functions.
“Obviously the remits are quite different, but the tool sets to implement those are fairly similar now. If you’re talking 10-15 years ago, the traditional buyside trader would be mostly phone-based, and they’ll be talking to somebody on the other end of the phone who will then be talking to a trader, and then the trader would work the order in the market most likely via an algorithm. That kind of separation of relationship is gone now. We have access to all those algorithms from various different brokerage houses so the need now to talk directly to an individual is less,” says Bray.
Going forward in the next four or five years, Bray says the involvement of technology in equity trading is only going to increase.
“On the systematic quant side, that is already happening. I imagine it will soon move into the more active trading space. In areas such as interaction with the market, we get sent IOIs (indication of interest) that brokers send to us as an indication of what they’re doing with other clients so we can match them. Things like that, I should imagine, will become a lot more quantitative,” Brays says.