High-frequency trading strategies that exploit today’s fragmented equity markets reduce investor profits overall, according to new findings by University of Michigan engineering researchers. The study is believed to be the first to examine how a common and lucrative trading practice known as latency arbitrage can exploit both market rules and the recent growth in the number of venues where stocks can change hands. The researchers will present the findings June 20 at the ACM Conference on Electronic Commerce in Philadelphia.
High-frequency trading firms use sophisticated algorithms and direct data lines to either predict market fluctuations or obtain early information about price changes. They’re responsible for more than half of all shares traded in U.S. stocks.
Latency arbitrage is a $21-billion-a-year tactic made possible by fragmentation—the shift from physical trading floors such as the New York Stock Exchange decades ago to dozens of competing electronic markets today. The strategy takes advantage of the time it takes for trade price information from the various markets to reach a central repository that publishes a public quote, known as the National Best Bid and Offer.
Established in 2005, this public ticker is one of several federal efforts aimed at reining in the effects of fragmentation. The Securities and Exchange Commission also mandates that the markets communicate and route orders to the place with the best price. But these efforts aren’t working as well as they could be, says Michael Wellman, U-M professor of computer science and engineering who led the study.
“The public ticker is always a little bit out of date,” Wellman said. “The delay is inherent. It takes time to compute and to disseminate the information. You can reduce the delay, but you can’t get it down to zero.”
High-frequency traders using latency arbitrage tactics look for price differences between the markets before the public ticker updates.
Read more at: Phys.org