When evaluating latency, it’s vital to consider all of the contributing factors, including the trade logic (the code that runs matching engines and algorithms), the speed of calculation hardware, the speed of telecom switch hardware, the quality and number of connections, and the distance between network nodes, according to Kevin McPartland, analyst at TABB Group. The industry as a whole is rapidly approaching the point where, “The code is so tight, hardware improvements are the main thing that will increase the overall efficiency of the operation,” McPartland says.
Enter vendors such as Blade Network Technologies (telecom hardware), Equinix (colocation hosting) and Nvidia (gaming graphics cards re-tasked to calculate derivatives). Each of these technology providers is feverishly trying to reduce the latency of its layer in the stack.
Santa Clara, Calif.-based Blade Network Technologies makes a 10 GB switch that connects feed handlers, algorithm boxes and matching engines at colocation centers, where firms have increasingly found it useful to situate their machines across the hallway from their counterparties, even if their offices and trading staff are on opposite sides of the globe. By merging routers with switches, Blade has eliminated a layer that previously added precious microseconds to a round trip, explains David Iles, Blade Network Technologies’ director of product management.
“We are providing sub-700 nanoseconds of latency, port to port,” Iles asserts. “We are also deterministic. You don’t want stale market data getting to devices. It has to take the same time to get from Port 1 to Port 24 as it does from Port 1 to Port 2.”
Technologies such as this tend to live side by side in colocation centers run by companies such as Foster City, Calif.-based Equinix. Here, the issue is bandwidth and energy efficiency, both of which are major cost contributors in the low-latency race. Trading firms are increasingly opting for colocation rather than running expensive, high-throughput dedicated fiber from their offices to the marketplace.
“We have a customer in Greenwich, Conn.,” relates John Knuff, general manager, global financial markets, at Equinix. “They were spending about $20,000 a month to get trades to New York. They moved a couple of cabinets in with us. It’s $3,000 to 5,000 a month for a cabinet, and $200 to $300 for the cross-connects. They essentially offset the cost of their colocation by getting rid of the network costs back to their office, which had no economic or competitive advantage.”
An equally important question pervades the minds of traders: Once you’re satisfied with the turnaround time to your market, how do you maximize the value of time between transactions? That question interested Tobias Preis, managing director of Artemis Capital Asset Management of Holzheim, Germany, to such a degree that he became one of the first customers of Nvidia’s graphical processing unit (GPU), a processor that has 480 cores, compared to the typical four- to 12-core CPU.
The GPU originally was developed to render high-resolution details for computer games. Preis, also a computational physicist, uses the GPU to calculate time series for the DAX-index futures algorithms that he deploys on Eurex.
“The increases in speed represented by the GPU are many times faster than the reductions in latency by the exchanges,” according to Preis, who says he gets by on 100 milliseconds to 150 milliseconds of average latency to Eurex. “We can now perform parallel-computing calculations that used to take one minute in one second.”
Where will low latency be in a year? Many market participants say they won’t be surprised if the discussion is about nanoseconds in a year. “I know we will break the 100 microsecond barrier,” NYSE’s Rubinow says. Beyond that figure, it becomes enormously expensive to add each zero behind the decimal point, he notes.
Despite the excitement over low latency and the extreme competitiveness of financial firms and the vendors that serve them, it’s important to keep a clear head about the need for speed, adds Adam Afshar, president of program trading at Atlanta-based Hyde Park Global Investments, which is 100 percent automated and has no manual traders.
“High frequency is just a method for implementing a strategy — it is not the strategy itself,” says Afshar. He notes approvingly that the decreasing cost of technology means that a $10 million investment in technology allows a smaller firm to rival the speed of the biggest banks on Wall Street.
But the key to success in the marketplace, according to Afshar, is adaptability, and that still comes from human ingenuity. For Afshar, going forward, the more interesting question is not “How fast can you hit the market?” but, “What do you do with that speed?”
“The bottom line,” he says, “is your adaptability to the non-linearity of markets.”