Twitter says it will beef up security for its users in response to recent breaches – one of which led to a major “flash crash” on Wall Street. We ask: what role do social media play on the markets?
The Frankfurt Stock Exchange may be one of the largest stock exchanges in the world – but with only about 3 dozen people on the trading floor, it’s hard to believe that millions of dollars exchange hands here.
That’s because most of the transactions are automated.
“It’s like the same distribution like you have in the airline sector where most of the airlines employ autopilot,” says Miroslav Budimir, an expert in capital markets at Deutsche Börse – the company that owns the Frankfurt Stock Exchange.
“There are so-called smart order routers, which basically take away the decision from the human and, on the basis of pre-defined criteria, send an order which they think is best at that moment in order to get the best price,” he adds.
The data on stocks and their best prices come from different sources, including the news.
News agencies like Bloomberg, Thomson Reuters and Dow Jones Newswires break down news items into categories by company, sector, product, product launch, or any other event that could have an effect on a given stock.
At the same time, there are computers that are programmed with algorithms, designed to look out for and react to these indicators.
And depending on what the indicator is, it can trigger a massive reaction.
That’s the art of machine based trading.
And with high-frequency trading, much of it comes down to speed.
“It’s certainly a good deal faster than one or two seconds, it’s more in the order of 10 milliseconds, so it has to be enormously fast for somebody to get a jump on it,” says Louis Lovas, director of solutions at OneMarketData, a company that produces a high-frequency trading system.
It all comes down to speed
The computers trade in and out of stocks all the time. Often the sum of money on an individual stock may appear to be very small – say, a few cents profit here or there. But with the volumes ranging in the millions and higher, a few cents profit on each stock can amount to a lot overall.
And when many computers react with a sudden sell-off – even for just a few cents – the large volumes of stocks they sell can lead to massive problems.
When this happens, traders talk of a “flash crash.”
The most recent flash crash was sparked by a fake tweet. It has since got a lot of investors thinking about the automated trading system.
Back in April 2013, hackers took control of the Associated Press news agency’s Twitter feed. The hackers caused a big scare when they sent out a tweet, suggesting the US president had been injured or killed in an explosion at the White House. All of a sudden – and for just a brief moment – the markets went into overdrive.
The fake news was corrected in minutes, but Wall Street had lost more than 100 points – $136 billion (105 billion euros).
Real news can also trigger a flash crash – it just depends on how worried it makes the traders and – more importantly – their automated systems.
In May 2010, the Dow Jones plunged 1,000 points – about 9 percent of its value – as a result of high-frequency trading systems selling aggressively amid the European debt crisis.
But Louis Lovas of Onemarketdata says the machines are not to blame.
“I know the finger has been pointed directly at algorithmic (machine-based) trading but it’s an arguable, debatable point whether that sort of initial reaction or that sort of sellout was initiated by human behavior or human emotional reaction, or machines, or possibly a combination of the two, which is probably the most likely candidate,” he says.
Making trading more secure
That’s why some regulators in Europe have stopped short of calling for an outright ban on machine based trading. Instead, they are pushing for a speed limit.
But before that happens, others are trying to figuring out how and whether social media – like Twitter – should be integrated in their algorithms.
“The use of social networks like Twitter or news feeds is really in its infancy,” Lovas explains. “Trading firms are suspicious of its value. And of course, this event that just happened with this Twitter hack is not going help things. If anything, it’s going to slow that process for any firm contemplating the idea.”
While that debate continues, Miroslav Budimir says there are measures at Frankfurt to prevent sudden dips in the market. He names “throttling” as one example.
“If we see that one member is flooding us with orders, we are able to throttle [restrict his traffic] until we eventually stop that order fully, or stop that member from trading,” he explains.
Throttling can prevent stock volatility – extreme price swings, up or down. But despite such measures, machine-based trading is far from perfect. And even Frankfurt has had bouts of sudden volatility in recent months – brought on by fast paced reactions to the news.