Data drives buy-side demand for low-latency infrastructure

More buy-side firms using algorithmic trading find low latency critical to their business, according to a recent Celent report.

More buy-side firms using algorithmic trading find low latency critical to their business, according to a recent Celent report.

In the report ‘Low latency: focus on cost and optimisation’, the research group said buy-side traders now have to deal with diverse data sources in near real time, with more data available for trading strategy formulation than ever before. As a result, traders are demanding greater flexibility from firms’ trading technology infrastructure to respond quickly to incoming market data.

The size of global data is expected to almost double each year for the next two years to reach 8 zetabytes, which means one sextillion bytes, from 2 zetabytes in 2011. Celent estimates that annual spending on real-time market data feeds was around US$19.4 billion in 2013, and says it is expected to grow by 3% to 4% over the next two years.

"Buy-side firms are looking at acquiring synchronisation, latency measurement and monitoring capabilities with greater interest," Muralidhar Dasar, analyst with Celent's securities and investments group and author of the report, said.

"With the increasing volumes of data that firms have to sift through, accurate time stamping is crucial to analysing temporal patterns in data."

According to Celent, the rise of algorithmic trading in recent years, especially in equities and derivatives, is a good indicator of how buy-side firms that consider low latency as critical to their business has expanded.

Despite cost constraints as a result of regulatory demands, the importance given to a low latency has not diminished, the report said. “The trading institution that hits the venue faster is still placed at an advantage.”

However, Matt Samelson, principal, director of equities at Woodbine, in an opinion piece, wrote buy-side firms “should go back to basics”, asserting that speed is only one factor in effective trading by institutional investors.

“We underestimate the real value of the experienced trader, over-rely on automation, and focus too much on distracting issues that just don’t matter,” he wrote. 

“The trading environment is certainly complex, but greater reliance on technology may not be the answer to mastering the markets. Better focus and smarter use of basic automation are the avenues to superior results.” 

Samelson said there should be a balance between human trading and effective algorithm use. “Humans should oversee complicated activity and only the most straightforward orders should be worked through algorithms.”