Machine Mania in the Marketplace: How Computers Came to Own the World

by David Haggith, The Great Recession Blog:

With 60% of stocks now being traded by bots that fake each other out in order to create buying opportunities, stock exchanges have lost their connection to the reason markets are created in the first place. The exchanges no longer exist as places for people to buy and sell ownership in a corporation. They exist simply as the neural junctions of a conglomerated machine that plays tricks on itself, and your sole goal is no longer to invest, but to put money in the slot machine that is the quickest trickster.

Many of the people who think of themselves as investors see this pretend investing as being almost risk free now that computers and central banks are running the racket. They put their money in the machines, and machines follow the central banks’ lead, purring along at historically low levels of market volatility as the machines run their automated tasks. A minority of market experts see a market that is building cataclysmic risks as it accumulates fake pricing that has nothing to do with intrinsic value and as the component machines keep getting reprogrammed to do a better, faster job of faking out the other machines.

 

[Brad] Katsuyama, whose firm and company were made famous by Michael Lewis’s 2014 book, Flash Boys: A Wall Street Revolt, says computers running complex software conducting trades at lightening speeds [are] a “dangerous” threat to the stability of the market, juicing volumes and sparking so-called flash crashes, where assets swing rapidly in value in a matter of seconds. “I think the biggest risk in the market is that 50-, 60-plus percent of the volume is being executed by computer programs who have no idea what companies actually do. They’re just reacting to data. And I think it’s dangerous.” (MarketWatch)

 

Katsuyama, whose company is starting its own stock exchange to try to combat the machines, blames rare bouts of volatility (flash crashes) on the computer algorithms that now dominate market trading. For example, when Amazon lost $40 per share in four seconds on June 9th this year and then immediately recovered, Katsuyama says you can be certain that didn’t have anything to do with a change in Amazon’s intrinsic value nor with any fundamental economic changes in this world. Some algorithm somewhere jogged a price switch and caused other algos to sing in harmony, flash-crashing Amazon’s stock and triggering a general decline in high-tech stocks. A computer glitch? Or arcane trickery by which the brainiest bot at that particular nanosecond managed to trick all the other bots in order to create a dip and then buy the dip and make billions?

Yes, there are enemy bots that know the other bots, find and exploit their weaknesses to trick as many as they can into selling in one direction in order to buy the trade in the other direction. In fact, a virtual lexicon of slang is gaining popularity with terms like “wash trade,” “layering” and “spoofing” for the kinds of micro teases and diversions and tricks employed by enemy bots.

 

In a “wash trade,” a trader acts as both buyer and seller of a stock, to create the illusion of volume. “Layering” and “spoofing” are off-market orders designed to trick the rest of the market into thinking there are buyers or sellers of a stock waiting in the wings, in an attempt to nudge the stock price one way or the other. (Vanity Fair)

 

During the financial crisis of 2007-2009 that brought down the world, only 30% of assets were traded by computer-generated trades. At double that amount, the next time will be different. Old-fashioned traders who research companies to buy stocks based on perceived company value now account for about 10% of the US stock market. There is very little concern in today’s trading for economic and business fundamentals.

Corporations are now just toys to be played with by the machines.

 

The strange new world of undefinable, self-programming bots

 

The scary part is that no one seems to know what causes specific flash crashes in many cases. Even Katsumaya only guesses at what really happened during the Amazon flash crash because visibility in the world of trader bots (or traitor bots) is zero. By that, I mean that even the people who create these algorithms truly have no idea what the bots’ current programming is because the programming is designed to be perpetually self-modifying through some vague crocodilian artificial intelligence created at the cerebral cortex of their semi-simian brains.

While no one seems to know the cause of Amazon’s flash crash, the Nasdaq ended 1.8% lower that day. The bots know best, though they actually know nothing at all. They merely respond to targeted stimuli.

It is the same in bond trading as in stocks. When the market for US treasuries flash crashed in 2014, it triggered extensive studies that revealed high-frequency traders (HFTs) were the culprits. Of course, HFTs are computers that place zillions of trades based on zillions of micro calculations every day.

Bear in mind that these auto-traders were mostly designed by young people, fresh out of college who have never known a bear market during their adult lives. The machines that determine the “market value” of all the corporations in our world were programmed by people who are only familiar with the dynamics of an always-rising, central-bank-driven market. How well the machines work if the market ever finds a way to slip into reverse, no one knows. The algos have never been tested in a true bear market as to how they might team up to accelerate the market’s decline. Since they were taken out of the box, they have been reprogramming themselves entirely based on bull-market dynamics. How they work running downhill is purely theoretical and unknown even then because of their self-programming nature.

But it will be fine. Trust the machines and their child creators who have little depth in the real-world markets.

Also unknown in this realm are the hackers lurking beneath these murky waters — be they anarchists or Korean agents or teenage savants seeking instant wealth — who might exploit the weaknesses and strengths of the machines in order seize ownership of the corporate world bit by byte or all in one colossal dump.