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Boffins from the University of Miami found that squadrons of "ultrafast" and out of control trading algorithms caused major spikes and crashes in the market. These dramatic events took place in less than 650 milliseconds - the period of time a chess grandmaster takes to notice that his king is in check.These automated banking machines operate at speeds that are far beyond human perception and the researchers found that the shorter these incidents became, the more often they occurred. They found that a huge cluster of "ultrafast extreme events" (UEEs) occurred just before the global financial crash of 2008 and particularly around 15 September of that year, when US financial services firm Lehman Brothers filed for bankruptcy.The number of UEEs also peaked during the Flash Crash of 2010, when the Dow Jones plunged by almost 10 per cent only to recover the losses within minutes. This event was the biggest one-day crash in the history of the Dow Jones Industrial Average, although it was different from a UEE because it lasted several minutes, rather than an imperceptibly tiny period of time.The report also said that competition between banks was driving a "billion-dollar technological arms race", with rivals trying to build faster and faster systems. This need for speed has seen banks invest in a transatlantic cable which shaves just five milliseconds off the time it takes to transmit data across the Atlantic. A chip called iX-eCute, designed for trading, can make calculations in just 740 nanoseconds (a nanosecond is just one billionth of a second).Discussing this "ultrafast machine ecology", Neil Johnson, professor of physics in the College of Arts and Sciences at the University of Miami and corresponding author of the study, said: "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."Our findings show that, in this new world of ultrafast robot algorithms, the behaviour of the market undergoes a fundamental and abrupt transition to another world where conventional market theories no longer apply."The researchers examined data relating to multiple stocks and exchanges, which revealed 18,520 spikes and crashes lasting fewer than 1.5 seconds between January 2006 and February 2011. These events are far too fast to have been caused by external factors, like bad news coming in from the wires or a change in regulations.Johnson suggested the situation could be compared to an ecosystem. "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," he added."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."There are relatively few things that an ultrafast algorithm will do," Johnson continued. "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 extreme events that we observe. Our math model is able to capture this collective behavior by modeling how these cyber mobs behave".The researchers were hampered in their work because they are unable to access "confidential exchange data" held by banks, which could expose how reliant the financial industries are on these algorithms.