These data feeds may be transmitted over fiber optic cable, microwave frequency broadcast, or via co-location at exchange server sites. Since HFT profitability depends on low latency, these and other financial firms have collectively invested billions of dollars in building upgraded high-speed data feeds.
High-frequency traders invest heavily to obtain the fastest networks and data feeds to gain a competitive edge in trading.
The biggest determinant of latency is the distance that the signal has to travel or the length of the physical cable (usually fiber-optic) that carries data from one point to another.
Since light in a vacuum travels at 186,000 miles per second, an HFT firm with its servers co-located within an exchange would have a lower latency—and hence a trading edge—than a rival firm located even a few miles away.
High-speed data feeds provide computerized algorithmic traders with faster more reliable data. Because HFT is driven by faster access to data, there has been a technological arms race, as data feeds and transactions approach the speed of light. HFT creates natural monopolies in market data, which critics say has given high-frequency traders an unfair advantage over institutional and retail investors.
Advocates claim HFT has a beneficial role in the market, deepening market liquidity and pricing securities more efficiently than other intermediaries, and lowering trading costs for everyone by tightening spreads. To maintain a fair and orderly market, the New York Stock Exchange (NYSE) introduced designated market makers in 2008 to facilitate price discovery and provide liquidity to both institutional and retail investors–much of it electronically through HFT.
The HFT industry has used many controversial predatory trading practices–as our guide to HFT terminology outlines–such as front running, where traders detect incoming orders and jump in front of them before they can be executed. Investors say that because there are so many HFTs in the market, it reduces long-run returns because they take a share of the profit.
Traders at banks and institutions began to see the effects of HFT on their large orders in the 2000s. The traders began noticing how their order flow appeared to be taken advantage of as stocks would race higher immediately after a trader began buying the shares. This caused institutional investors to have to chase the stock in order to get filled. The HFT firms would see the order flow demand and buy shares ahead of it, with the aim of selling sell the shares back to the investor at a higher price. It wasn’t until years later that many of the investors learned of what exactly was happening, thus they had to learn to deal with HFTs in the years afterward.
Bloomberg’s B-PIPE data feed, Thomson Reuters’ Matching Binary Multicast Feed, and EBS Brokertec’s Ultra are examples of high-speed feeds, which provide investors and vendors market data with extremely low latency–the time that elapses from the moment a signal is sent to its receipt.
The stock market now consists of a vast fragmented network of interconnected and automated trading systems. HFT, characterized by high speeds, ultra-short holding periods, and high order-to-trade ratios, comprises a 50% share of U.S. equity trading volume, which is significant but less than the over 60% share recorded in 2009. Smaller volumes, low market volatility, and rising regulatory costs have compressed HFT margins and led to consolidation in the industry.
To address issues of exchange competition, regulators have introduced speed bumps that randomize entry times and introduce random order processing delays. After the new IEX exchange introduced its alternative trading system, which slows orders by 350 microseconds to neutralize high-frequency traders’ advantage, the New York Stock Exchange followed suit in 2017 on its exchange for small and mid-cap companies.