Trading Firms Look Beyond Low-Latency

Terry Flanagan

As low-latency connectivity becomes more commoditized, trading firms are looking at other sources of completive advantage, such as cost reduction and Big Data analytics.

“With trading profits down substantially and HFT under significant pressure to survive, let alone thrive, infrastructure specialists are putting more emphasis on cost-containment and reduction,” said Shawn Kaplan, general manager of financial services at data center provider Telx. “With a dense concentration of counter-parties in the key data centers the cost of connectivity has dropped substantially.”

Telx is set to unveil a flagship campus in Clifton, N.J., called NJR3, that will provide an ideal location for back-testing engines, back-office systems, development and other trading support systems, Kaplan said.

In February 2013, the NYSE opened up its doors to carriers other than its proprietary SFTI network which had previously been the only way in and out of the building.

“It turns out that the fastest fiber route between the NYSE Mahwah datacenter and the other equity exchanges ran directly behind the Telx Clifton campus. “It also turns out that Telx sits precisely between the two leading equity markets, NYSE and NASDAQ, making Clifton not only a lower cost trading hub, but also a low-latency proximity hub for the financial markets,” Kaplan said.

But not everyone in financial services needs low-latency connectivity. Most long/short hedge funds, regional banks, wealth advisors, and asset management firms care more about reliability and security than trading performance, he said.

Many firms are still locating their data centers inside of their corporate offices in Manhattan or New Jersey. “Seldom does good office space also make good datacenter space…in fact, almost never. Hurricane Sandy showed us just how fragile many firms’ business continuity plans really are.

The explosion of Big Data, meanwhile, has affected all industries, but the capital markets has its own unique set of issues, such as the need to capture time-series data and merge it with real-time event processing systems.

“We see a fundamental shift in focus from low latency to Big Data,” said James McInnes, CEO of trading platform provider Embium. “It’s not about being the fastest, but about being able to process tons of data. Lower trading volumes have forced people to trade multiple asset classes, which means more data to analyze.”

Embium’s foundation for automated trading was built around a desktop automation solution that enabled retail traders to rapidly develop strategies. “We have since evolved the technology and in the process, created a new trading engine to effectively serve global financial institutions,” said McInnes. “Our focus has shifted to flexible strategy development and highly scalable, server-side automation solutions for low latency executions.”

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