The company offers its platform to customers, but, just as importantly, it gives them application programming interfaces that make it easy for them to develop their own software on top of it. That allows PhaseCapital (which won’t disclose how much it pays for StreamBase’s platform) to apply its own algorithms for scrubbing data and making trades.
Typically, PhaseCapital processes 30,000 to 40,000 “ticks,” or pieces of market data, per second. During the flash crash, that number jumped to more than 289,000 ticks per second—much of it representing stocks swinging wildly. “A lot of scrubs kicked in and realized that this data didn’t make sense,” Yu says. For example, some large publicly held companies, such as Accenture, traded for less than $1 during the flash crash. PhaseCapital continued trading, but filtered data that appeared suspicious. Because it didn’t act on that data, it was spared erroneous trades.
Even though many trades were later canceled, Eric Pritchett, PhaseCapital’s CEO, says there are several key reasons that it was important to avoid them anyway. For one thing, he says, it’s never certain what criteria regulators will use to cancel trades, so he wouldn’t want to have to rely on that mechanism. More importantly, he says, erroneous trades throw off a firm’s behavior for the rest of that day. For example, if a trade appears to have been profitable, algorithms may determine that the firm can afford to take riskier actions than it otherwise would. Pritchett says, “Not knowing where you really are with your book and your risk is the number one most dangerous thing that can happen to a trading firm.”
The example illustrates that anomalies in markets present both risks and opportunities, says Adam Honoré, who focuses on financial services technology as research director of the institutional securities practice for Aite Group. And the volume of data involved in trading is only going to increase, he notes.
Any time a company wants to analyze more data, there’s generally a price to pay—the extra processing reduces the speed at which a firm can take action. StreamBase has been a powerful tool in PhaseCapital’s eyes because it is structured so that new data can be filtered without causing significant performance hits, Yu says. “The trick to this game,” he says, “is to be fast and smart.”