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Mammoth mystery algorithm on Nasdaq: who and why?
A single algorithm which placed and then cancelled orders on the Nasdaq accounted for 4% of all quoted traffic in the US with no clear goal. An investor gives FRANCE 24 his insight into the mystery which has concerned market watchers.
A single mammoth mystery algorithm has set alarm bells ringing for market regulators and players, and underlined the market’s vulnerability to technology and the woeful lack of regulation on algorithms.
A single algorithm last week placed and cancelled orders on the Nasdaq accounting for 4% of all quoted traffic in the US. Not only this, it also accounted for a colossal 10% of the bandwidth that is allowed for trading on any given day.
It placed orders in 25-millisecond bursts, involving approximately 500 stocks, but never actually executed a single trade.
The algorithm’s stopped operating at 10.30am ET on Friday.
Market players are now scratching their heads as the point of this huge market play which did not execute a single trade.
An anonymous French investor who goes by the name of LC and writes the blog Margin Call www.margincall.fr, told FRANCE 24 in a telephone interview, “This system had numerous unusual features: the main one being the sheer number of orders placed.”
One thing is for sure: the operation was not designed to make money. Executing no actual transactions, the programme had no effect on the stocks involved. “Simply flooding the system with orders looks like a way of testing the limits of the algorithm,” LC explained.
Jon Najarian, co-founder of TradeMonster.com, agreed. “My guess is that the algo was testing the market, as high-frequency frequently does”, Najarian told CNBC.
Hungry for high-frequency trading
Another explication could be that the architect behind the operation was seeking to create an imbalance in the market. The orders generated by the algorithm used up 10% of the Nasdaq’s daily quota of bandwidth. “Hogging such a big chunk of available space inevitably slows down the system, giving a lead to trading floor operators, because everybody else receives data with a delay of a few seconds,” LC explained. “It’s a raw deal for the others, but for now, there’s no law against placing orders at such a high frequency.
“This only goes to show just how big a part IT plays in financial activity,” he went on to say. “Through the large number of transactions executed automatically – and bearing in mind that stock market operators receive a commission for each one, financial markets have become hugely dependent on high-frequency trading. It now represents 31% of the New York Stock Exchange’s revenue and 17.1% of Nasdaq’s.”
This dependence could explain why little has been done about these algorithms that can and do create significant market volatility. Profit-hungry stock markets would rather turn a blind eye to anomalies than scare away potential HGT aficionados, LC explains on his blog.
But a laissez-faire attitude to high-frequency trading remains a risky business for traditional stock markets, as demonstrated by the alarming Flash Crash two years ago.
On 6 May 2010, the Dow Jones Industrial Average plunged 9.2% in the space of just ten minutes.
The crash, unprecedented in the history of Wall Street, was caused by a mass of orders placed using software. But even after an investigation by the Security Exchange Commission (SEC), no measures were taken against algorithmic trading.
However, the US regional Federal reserve bank did issue a warning on September 18th aimed at high-frequency trading firms who take shortcuts in their risk controls as they seek out faster ways to trade.