High-Frequency Strategies
Of course, these high-frequency participants do not all follow the same strategies. Iati breaks the various high-frequency trading strategies into five broad categories.
With arbitrage strategies, Iati explains, traders look to correlate prices between securities in some way and trade off of the imbalances in those correlations. "Those imbalances can and do occur in microsecond time frames," he comments. "The more time that elapses, the more time for those imbalances to be corrected. A trader who can achieve [just] a millisecond of latency can capture some of that opportunity."
Pairs trading, and more specifically cross-asset pairs trading, also is a popular high-frequency trading strategy, according to Iati. "For example, if I am looking at a correlation between Coke and Pepsi -- if one moves up one would expect the other to move up," explains Iati. "Or, in the case of cross-asset pairs, the correlation between the derivative and an underlying asset. So the price of each is tied together. High-frequency traders continuously calculate the value of both, looking for an imbalance."
Another high-frequency strategy is volatility trading or trading on relative price movement rather than absolute price movement. In this case, Iati says, "Traders make money on volatility, not necessarily on movement."
The last -- and most controversial -- type of high-frequency trading, according to Iati, is "liquidity detection." "This is when firms are looking to decipher whether there are large orders existing in a matching engine by sending out small orders, or pinging to look for where large orders might be resting," he relates. "When a small order is filled quickly, there is likely to be" a large order behind it.
Iati points out that firms trade variations or combinations of these strategies. "Many of these are not completely independent," he says.
Karpman of Trading Strategy Group says his firm's use of high-frequency trading strategies mostly aims to take advantage of arbitrage situations. "We also recently have gone into sentiment trading, or analyzing news and reactions to the news," he relates. "All of the data is stored in a very fast algorithm, and once a new piece of data or news comes in, a decision is made in milliseconds on how to act on the news." In other words, as soon as a news event is reported, it triggers the algorithm and automatically shoots an execution order.
In addition Trading Strategy Group also conducts high-frequency trading around pairs trading strategies. "If we see certain movement from one security to another, and we know universally they should have some kind of fixed spread between them but we see a large deviation, then we make a move," Karpman explains, adding that these types of trades are easier to track because there isn't a lot of data to analyze.
"Whenever we can do the prep work beforehand and then just react on the information as it comes in from the market, those are the strategies I would characterize as high-frequency -- and they are always active," Karpman comments. "If there is a little piece to grab, we'll grab it."
According to Bank of America Merrill Lynch's Michael Lynch, "High-frequency trading has been around as long as there has been electronic trading, but now it's associated with latency levels we've never seen before."
"I remember sitting on the desk years ago, and because I had a Bloomberg terminal and my clients didn't, I could call them and tell them X company had just reported earnings. That's faster than the investor who waited until the next day to read about the earnings announcement [in the newspaper]," he continues. "Information content has always driven markets, and that is a good thing. Liquidity has always driven markets, and that's a good thing."
