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ZeroHedge: Stock Market Crashes Since 2006: Trading Bots

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Taking a guess is always a stupid game as it’s a game of luck hitting the right number. Hazarding a guess as to how many jelly beans in the jar is nigh-on impossible. We might normally think that it has nothing to do with any mathematical correlative analysis but just a number that has been magicked out of the air by some person. Don’t be fooled however as there are ways of getting you closer to that number. But, if you were asked to guess the number of stock-market crashes that have happened since 2006, then what would you put forward as your best answer? You might not win the jelly beans in that jar, but you probably won’t be anywhere near close to getting the number of crashes that have taken place around the world.

Since 2006, there have been a total of 18, 520 crashes, mini-crashes and flash-crashes or flash freezes (we have more names than we know what to do with) since that year. Most of them probably went unnoticed, since they were less than a blink of your eye and we didn’t know that they had happened.

New research has analyzed historic trading and has discovered that it is the automated systems that are at the heart of the problem.

High-Frequency Trading

  • High-frequency trading systems are computerized analyses that enable the searching for small modifications and differences in stock prices that may be used to gain high-profits when combined in high-numbers.
  • If enough is invested and across the whole range of minor differences that are recorded in stock prices, then the gains are unimaginably.
  • There is minimum human surveillance of such systems as their advantage is that they occur in record times that no human brain or person could compete with them to execute buy or sell orders.
  • No human being could monitor the systems anyhow, since the delay-time necessary to react by a human being would be much slower than the order that gets processed via the technology.
  • However, the systems lead to up or down swings in the stock market that are extreme.
  • Traders usually follow such swings and use the automated systems to react in turn, with a time-delay to the orders that are executing themselves.
  • This, in turn, leads to even greater swings, sometimes quite violently, that are recorded on the stock markets around the world.

The new type of trading that has been rushed in with the automated systems that are able to compute price changes reached fever pitch at the start of the financial crisis in 2008 according to the research.

  • Speed is the essence of the programs that analyze micro-changes in the stock market.
  • The human brain can only calculate and react after a one-second lapse in time when considering what is taking place.
  • Computerized systems have the ability to calculate in about 740 nanoseconds, which means about 1, 000times faster than the human brain.
  • Even a chess-player (who usually reacts after 650 milliseconds) wouldn’t be able to do anything against the systems that have taken over trading.

What is essential in the system is the fact that short, small changes that are not going to last must be spotted and orders placed before that change moves on and disappears. Today those systems are becoming faster and faster and advantage is being taken of new technological prowess that is being invented in the field of optic-fiber cables and software analysis. This new technology will enable another 5 milliseconds to be removed from the calculation time necessary to place the order. Does that mean that the stock markets risk becoming even more open to volatility and crashes in the future when it starts being used?

Ultrafast Extreme Events

Ultrafast Extreme Events is the name that is given to the movement of stock prices that move ten times or more either up or down (but always in the same direction) and always within 1, 500 milliseconds. The 18, 500 crashes that have gone unnoticed to the human brain all occurred in time-spans that were below the one-second time necessary for the human brain to react. This means that they were not primarily caused by traders. They were perhaps exacerbated when the traders decided to follow in the footsteps of the high-frequency-trading systems, but it was those systems that caused the problem.

The technology to act and to react in record-setting time has been invented. But, the technology has today surpassed our own ability to monitor the system. Technology that is faster than the systems that execute the orders to buy and sell will end up having to be invented. But, that will mean a never ending race to be one-step ahead of the technology that we are using to monitor minor fluctuations in the stock prices. The number of ultrafast extreme events has continued to increase since these computerized systems were first introduced in 2006.

Fast-trading and computerized systems coupled with a drop below the 1-second time zone mean that the stock market is open to greater volatility today. The threshold of 1 second was crossed years ago now with these systems becoming part and parcel of trading. The number of strategies used by traders has also dropped. So, speed and limited-trading strategies are the source of the problem and not the financial factors of old that may have resulted in the volatility of certain shares. Today shares move massively because the systems take advantage of minute variations. The only thing that could modify that is a marked change in the technology used and the way it is being used.

Algorithm Predators

The findings of the research carried out by Neil Johnson, professor of physics at the College of Arts and Sciences at the University of Miami (UM) show that the algorithms are the source of the problem because humans cannot keep up with them: “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”.

Conventional market theories are thrown out of the window at this point it would seem and we don’t even know what has hit us. Johnson went on to say: “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 event. 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”. The predators are here to stay, but who will pay the price for that? Simple question and an even simpler answer. Johnson believes that 2006 was the era of the cyber mob that is the new predator on the stock market.

Artificial Intelligence and Trading on the Stock Market

Man can be his own worst enemy sometimes and technology has left the people behind. Artificial intelligence that sends a shiver down your spine like a science-fiction movie that you thought could never come true. It’s the robots and the algorithms that are running the markets today and not the human beings that have invented them or the people that hand over their money to invest on the stock-price movements. The movements and the changes in the stock market are so fast that human beings and traders are out of the loop just watching. It’s only the programs that have been invented that end up battling it out between themselves to gain control and improve their chances of profit. This is at least true of subsecond transactions. Some might certainly argue that if the traders are ineffective, we might just as well get shot of them.

The algorithms earn profits of thousands of dollars every millisecond. That’s nothing for sure in the world of finance, but added together it means millions every second. No trader could do that. It’s ok if you win and come up trumps. But, winners always mean losers somewhere else. The losers might just be ourselves with the pension funds and the investments that are linked to the stock market.

It was the banks that first started using those systems in order to make greater profits. But, the banks that suffered the highest number of Ultrafast Extreme Events were also the ones that went bankrupt and had to be bailed out.

They invented them, they used them, but the rest of us paid the price for them! We’re still paying the price, aren’t we?

The research was carried out by Guannan Zhao (post-doctoral researcher at UM), Hong Qi and Jing Meng (Ph.D. researchers in Physics at UM), Nicholas Johnson (Professor of Physics at UM) and is entitled “Abrupt rise of new machine ecology beyond human response time.”

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