Researchers find sudden rise of global ecology of interacting robots that trade on markets at speeds too fast for humans

Robots take over
Typical ultrafast extreme events caused by mobs of computer algorithms operating faster than humans can react. See for more examples. Credit: Neil Johnson, University of Miami

Recently, the global financial market experienced a series of computer glitches that abruptly brought operations to a halt. One reason for these "flash freezes" may be the sudden emergence of mobs of ultrafast robots, which trade on the global markets and operate at speeds beyond human capability, thus overwhelming the system. The appearance of this "ultrafast machine ecology" is documented in a new study published on September 11 in Nature Scientific Reports.

The findings suggest that for time scales less than one second, the financial world makes a sudden transition into a cyber jungle inhabited by packs of aggressive trading algorithms. "These algorithms can operate so fast that humans are unable to participate in real time, and instead, an ultrafast ecology of robots rises up to take control," explains Neil Johnson, professor of physics in the College of Arts and Sciences at the University of Miami (UM), and corresponding author of the study.

"Our findings show that, in this new world of ultrafast robot algorithms, the behavior of the market undergoes a fundamental and abrupt transition to another world where conventional market theories no longer apply," Johnson says.

Society's push for faster systems that outpace competitors has led to the development of algorithms capable of operating faster than the for humans. For instance, the quickest a person can react to potential danger is approximately one second. Even a chess grandmaster takes around 650 to realize that he is in trouble – yet for trading can operate in a fraction of a millisecond (1 millisecond is 0.001 second).

In the study, the researchers assembled and analyzed a high-throughput millisecond-resolution price stream of multiple stocks and exchanges. From January, 2006, through February, 2011, they found 18,520 extreme events lasting less than 1.5 seconds, including both crashes and spikes.

The team realized that as the duration of these ultrafast extreme events fell below human response times, the number of crashes and spikes increased dramatically. They created a model to understand the behavior and concluded that the events were the product of ultrafast computer trading and not attributable to other factors, such as regulations or mistaken trades. Johnson, who is head of the inter-disciplinary research group on complexity at UM, compares the situation to an ecological environment.

"As long as you have the normal combination of prey and predators, everything is in balance, but if you introduce predators that are too fast, they create extreme events," Johnson says. "What we see with the new ultrafast computer algorithms is predatory trading. In this case, the predator acts before the prey even knows it's there."

Johnson explains that in order to regulate these ultrafast computer algorithms, we need to understand their collective behavior. This is a daunting task, but is made easier by the fact that the algorithms that operate below human response times are relatively simple, because simplicity allows faster processing.

"There are relatively few things that an ultrafast algorithm will do," Johnson says. "This means that they are more likely to start adopting the same behavior, and hence form a cyber crowd or cyber mob which attacks a certain part of the market. This is what gives rise to the that we observe," he says. "Our math model is able to capture this collective behavior by modeling how these cyber mobs behave".

In fact, Johnson believes this new understanding of cyber-mobs may have other important applications outside of finance, such as dealing with cyber-attacks and cyber-warfare.

The study is titled "Abrupt rise of new machine ecology beyond human response time."

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Study links ultrafast machine trading with risk of crash

Journal information: Scientific Reports

Citation: Researchers find sudden rise of global ecology of interacting robots that trade on markets at speeds too fast for humans (2013, September 11) retrieved 22 October 2019 from
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Sep 11, 2013
As long as you have the normal combination of prey and predators, everything is in balance, but if you introduce predators that are too fast, they create extreme events

Yep. An instant/ubiquitous predator will create instant extinction (i.e. a market crash).

Simpler algorithms are faster. And if you're faster than the competitor then that means you're the first to react (and the first one to reap the profit...whereas the slower ones may even make a loss by their 'slow' prediction, because the situation was changed by the fast 'predators' in the time between when they got their datapoints and when they reached their decision).
Taken to an extreme this means linear extrapolation from the last two datapoints is the fastest possible algorithm to make money. And any engineer can tell you what happens when you let such an algorithm loose in wide-area-effect manner in a complex environment.


Sep 11, 2013
and yet they produce nothing and create no wealth, why not apply them to carbon trading?

Sep 11, 2013
and yet they produce nothing and create no wealth, why not apply them to carbon trading?

Already way ahead of you.

Some guys at Deutsche Bank did that in 2009-2010. Trading carbon emission certificates at top speed in a circle (intra-EU to extra-EU). In every cycle they generated cash for themselves by evading taxes.

The original intent of a stock market has long been lost. Right now it's just a method of skimming off of other people's work. If you think you can reliably make money on the stock exchange as a privat investor (unaugmented by super-fast computer-trading) then you're just kidding yourself.

Sep 11, 2013
18,520 events in under 1900 days...not all of which wer trading days.

Sep 11, 2013
I've noticed these activities in the metals markets

-with crashes followed immediately by spikes and vice versa. It's almost like these predators are feeding on each other, anticipating event-driven strategies and then feeding on them. Is this an ominous sign of the end of markets? When will these programs begin to self-improve and innovate?

The digital equivalent of the Hunt bros could destroy an entire sector instantly.

Sep 11, 2013
Ultra-fast does not imply simple and easy to understand. With massively parallel computing, answers can arrive fast and the algorithm be almost incomprehensible to follow since it involves the interactions of many independent and asynchronous processes.

Sep 11, 2013
The speed issues are really down to individual cycles at this point.
Banks and trading houses are already installing direct laserlines because the lag due to sattelite communication is already making them too slow. Location close to trading centers are at a premium.
It's gotten quite ridiculous, really.

Sep 11, 2013
So, the first thing that came to my mind is that if there is a 1.5 second crash, then someone is buying during that 1.5 seconds to take it out of the crash. And if there is a 1.5 second spike, then someone is selling at that spike to return the market to normal.

A very simple program that looked for sudden leaps of over three standard deviations one way or the other could make you a lot of cash, now that we know such leaps occur.

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