It seems like everyone defines "high-frequency trading" slightly differently. Ask 10 industry veterans and you'll get 10 variations on a similar concept. But while it may be difficult to pin down an exact definition of high-frequency trading, there are definite characteristics that help define the trading strategy.
First, high-frequency trading depends on speed of execution and ultralow latency. That generally is coupled with a very high trading turnover -- many trades taking place over a short time period. Finally, high-frequency trading shops take few, if any, overnight positions as they are focused on the accumulation of small, short-term profits.
"High-frequency trading involves the large-scale turnover of numerous positions, making a small return on each turnover," explains Matt Samelson, principal at Woodbine Associates, a capital markets research and consulting firm focusing on equity market structure, adding that highly sophisticated low-latency technology is the backbone of any high-frequency trading strategy. "You want to have algorithms that are based on good models," he says. "Then you need to have fast computational technology to calculate and run the models, and then you need to have the ability to execute on a high-speed basis."
In addition, Samelson notes, high-frequency trading generally leverages participants' proprietary money. Although some high-frequency shops offer to hedge funds the infrastructure to enable low-latency executions for high-frequency strategies, he says, high-frequency trading is not conducted on an agency basis.
According to Robert Iati, partner and global head of consulting at TABB Group, "We define high frequency as fully automated trading strategies that seek to benefit from market liquidity imbalances or other short-term pricing inefficiencies. And that goes across asset classes, extending from equities and derivatives into currencies and a little into fixed income."
Iati also makes the distinction that high frequency trading shops depend on hundreds of algorithms and he has even heard of policies to never let an algorithm go longer than four to six weeks without being changed in some way. "They are paying millions of dollars to coders to build a hundred variations of a particular algorithm or series of algorithms. That was eye opening," says Iati.
Contending that high-frequency trading is "just a label," Rishi Narang, founding principal of Telesis Capital, a Southern California-based alternative investment manager focused on quantitative trading strategies, attempts to define the strategy by what it is not: "If you take home overnight positions, and if trading turnover is not north of 100 percent per day, then you're probably not really high-frequency trading in aggregate," he asserts.
Eric Karpman, CEO of Trading Strategy Group and Luxoft Trading Solutions, adds that high-frequency trading requires immediate, real-time data analysis, which leads to automatic trading decisions. "It means analyzing what is happening in the market on the spot -- without the time to store the data in a database -- doing automatic tick-by-tick analysis and making decisions based on that," he adds.
"It's a natural evolution in the market," says Michael Lynch, managing director and head of Americas Execution Services at Bank of America Merrill Lynch. "It follows the analogy of what used to happen on the exchange floor, but it's updated for speed, technology and market structure today."
Clearly, "There is no one definition to high-frequency trading," points out Ruth Colagiuri, head of electronic products at Bank of America Merrill Lynch. "Rather, there is an enormous range of speed of access to the market, volume traded and styles of trading that are not well understood by many observers."
Nonetheless, Telesis Capital's Narang argues that there even is a subcategory of high-frequency trading -- ultrahigh-frequency trading -- that is extremely sensitive to latency down to milliseconds and microseconds. "Most of the chatter out there now is really about ultrahigh-frequency trading, when colocation really matters and shaving off milliseconds is important," he says. "It doesn't matter nearly as much for generic short-term quantitative trading."