( CNN ) -- If you have ever tried to grab a bargain that appears online , you 'll know you have to be quick . The business of high frequency trading -- using algorithms and superfast computers to conduct trades in a fraction of a second -- is a supercharged version of this , with the potential to execute millions of buy and sell orders electronically each day through the myriad exchanges currently in existence . Advocates argue that high frequency trading reduces market volatility and lowers transaction costs for small investors , but others claim it is unfair on slower traders , and can lead to instability -- trading algorithms and high frequency trading were behind the `` Flash Crash '' of May 6 2010 , when the Dow Jones briefly plummeted almost 1,000 points . Irrespective of how the popularity of high frequency trading changes in the future , this need for speed will continue to drive a technological arms race where the weapons of choice include new types of computer circuits hard-wired with dedicated trading algorithms ; new tunnels blasted through mountains to ensure more direct optic fiber connections ; new cables being laid in straighter paths across the Atlantic seabed ; and even new networks of microwave towers to profit from the speed of electromagnetic signals through air . And as the search for an evolutionary edge continues , `` genetic '' trading programs will be created that develop specific mutant offspring in response to real-time changes in market conditions . Even long-term pension funds play the high frequency game , hence it involves us all -- whether we like it or not . There is one factor that limits speed : According to Einstein , nothing can travel faster than the speed of light . However this leaves ample opportunity for future increases in trading speed . Light can travel approximately one foot in a nanosecond ( a billionth of a second ) in free space , meaning that current processers , routers and switching devices have plenty of room for improvement . And just as faster predators in the animal kingdom catch more prey and will be less vulnerable to other predators , faster trading companies will emerge at the expense of slower ones . In parallel , a new form of ultrafast options market may emerge with second-scale contract times in order to hedge high frequency risk . However , there are two problems that make the future of high frequency trading of unique global concern , irrespective of how popular it becomes . The first is a scientific one : Financial markets represent the largest-ever sociotechnical system in existence , with a mix of state-of-the-art communications and computational power operating at speeds approaching the natural speed limit of light . Yet nobody , including Einstein , has ever produced a theory that predicts what might go wrong in an ultrafast global network of interconnected machines that carry out millions of operations in the blink of an eye -- or what can be done to prevent or manage it . This leads to the second problem . How can regulators and governments possibly decide how to manage this emerging ultrafast financial jungle if nobody yet fully understands it ? My fellow researchers and I recently uncovered glimpses of what is already going wrong in the form of escalating patterns of `` sub-second tsunamis . '' These tsunamis are huge spikes and dips in the price of an individual stock . Although the Flash Crash was fast , lasting only a few minutes , these sub-second tsunamis are over in the blink of an eye -- and there are thousands of them . A 10 % daily change in a major stock would guarantee breaking news coverage , but these tsunamis typically send the price plummeting to almost zero . However they go unnoticed since the price quickly recovers as other algorithms jump in for the kill . Their existence reveals a remarkable difference between the human trading world above the typical human response time of one second , and the all-machine ecology of trading algorithms below one second . Just like cracks propagating in a structure prior to mechanical failure , these sub-second tsunamis escalated in the lead up to the 2008 financial meltdown . Most importantly , the stock showing highest proliferation are the banks that are now associated with the crisis . Yet nobody knew at the time . Indeed our research predicts a growing zoo of such tsunamis in the future , with each species having its own characteristic twist and turns . Governments need the financial equivalent of an air traffic control system in order to know how to manage this brave new world , and hence what rules ( if any ) to impose . This in turn will require a joint research program between trading houses , regulators and academics . However , instead of using conventional economics , the methodological approach should be built around complex adaptive systems and dynamical networks . Generative market models must be tested in real-time against high resolution data , to see if they can reproduce the observed price exchange dynamics down to the sub-second scale . Our own research predicts that these sub-second market movements will be neither completely unpredictable nor predictable , but will instead have pockets of predictability that come and go in particular ways . Estimates of the market share of different trading algorithms will enable real-time system management , while ensuring that the secrecy of individual trading entities remains intact . Without such a financial Manhattan Project , regulatory bodies will effectively be flying blind and may end up doing more harm than good . Read this : How to start your own currency . Read this : Would you bank with Starbucks ? The opinions expressed in this commentary are solely those of Neil Johnson .
High frequency trading uses computers to conduct trades in fractions of a second . It can cause individual stock prices to spike and dip close to zero , says Andrew Johnson . These ` ` sub - second tsunamis '' go unnoticed and are over in the blink of an eye . We need a financial ` ` air traffic control ' '' to manage this , says Johnson .