The theme of many sci-fi scripts is the abandonment of the human dimension for that of the machine.
One aspect of that theme is the elimination of the human factor entirely as giant computers take on a life of their own, become sentient and resolve to exterminate the human race, which is needed no longer.
Welcome to the new reality on Wall Street, which is no longer dominated by human analyses, but which is increasingly dominated by computers which specialize in complicated algorithms which determine the rise and fall of global markets.
Felix Salmon and Jon Stokes, in their article “Algorithms Take Control of Wall Street,” are among the latest authors outlining the promise and perils of unregulated computer control of stock markets.
Computers have the ability to store more data and to transfer it at speeds impossible for humans to replicate, though it is still possible for humans to “control’ the machines and put them to work to their advantage.
The abilities of computers for lightening fast absorption and actionable information has resulted in a new service known as “Lexicon,” which has clients who are algorithms, “lines of code that govern an increasing amount of global training activity.”
How does it work?
Lexicon scans every Dow Jones stock record with the immediacy only computer speed can accomplish, and look for clues that indicate the ups and downs of the investors. “Then it sends the slight variants in “emotive” behavior of investors back to computer subscribers who can break it down in order to make decision about their buying patterns.”
The lengthy evaluative process humans once had to make for themselves—reading the news and making personal evaluations, is not just abbreviated. It’s eliminated. The machines make the decisions.
Welcome to the new Wall Street, where screaming floor traders are no longer “actionable.”
Salmon and Stokes write that the entire financial system has been taken over by algorithmic trading. “From the single desk of a startup hedge fund to the gilded halls of Goldman Sachs, computer code is now responsible for most of the activity on Wall Street…Increasingly, the market’s ups and downs are determined not by traders competing to see who has the best information or sharpest business mind but by algorithms feverishly scanning for faint signals of potential profit.
Algorithms have become so ingrained in our financial system that the markets could not operate without them.”
It’s enough to make a mere human being break out into a cold sweat.
But for Washington, determined to bring Wall Street under its control, the algorithmic finesse of computers means trading, always a volatile and elusive mess, is a regulatory nightmare, as it is no longer humans who are to be regulated.
And, frankly, show me the congressman who understands the new trading systems.
What is understood, no matter how vaguely, is that the algorithmic method produces extreme volatility.
As the authors point out, “individually, these algorithms may be easy to control but when they interact they can create unexpected behaviors—a conversation that can overwhelm the system it was built to navigate. On May 6, 2010, the Dow Jones Industrial Average inexplicably experienced a series of drops that came to be known as the flash crash, at one point shedding some 573 points in five minutes. Less than five months later, Progress Energy, a North Carolina utility, watched helplessly as its share price fell 90 percent. Also in late September, Apple shares dropped nearly 4 percent in just 30 seconds, before recovering a few minutes later.
These sudden drops are now routine, and it’s often impossible to determine what caused them. But most observers pin the blame on the legions of powerful, superfast trading algorithms—simple instructions that interact to create a market that is incomprehensible to the human mind and impossible to predict.
For better or worse, the computers are now in control.”
Also, for better or worse, academics—math, science and engineering whiz kids—are now in charge as they have begun applying algorithms to “every aspect of the financial industry. Some built algorithms to perform the familiar function of discovering, buying, and selling individual stocks (a practice known as proprietary, or “prop,” trading). Others devised algorithms to help brokers execute large trades—massive buy or sell orders that take a while to go through and that become vulnerable to price manipulation if other traders sniff them out before they’re completed. These algorithms break up and optimize those orders to conceal them from the rest of the market. (This, confusingly enough, is known as algorithmic trading.) Still others are used to crack those codes, to discover the massive orders that other quants are trying to conceal. (This is called predatory trading.)
“The result is a universe of competing lines of code, each of them trying to outsmart and one-up the other. ‘We often discuss it in terms of The Hunt for Red October, like submarine warfare,” says Dan Mathisson, head of Advanced Execution Services at Credit Suisse. ‘There are predatory traders out there that are constantly probing in the dark, trying to detect the presence of a big submarine coming through. And the job of the algorithmic trader is to make that submarine as stealth as possible.’ ”
So while the smart kids devise the algorithms, the algorithms tend to take on a life of their own, seeing the market from a computer’s point of view, “which can be very different from a human’s. Rather than focus on the behavior of individual stocks, for instance, many prop-trading algorithms look at the market as a vast weather system, with trends and movements that can be predicted and capitalized upon. These patterns may not be visible to humans, but computers, with their ability to analyze massive amounts of data at lightning speed, can sense them.”
So the statistical minutiae computers can separate and sense patterns which then determine within milliseconds the buying and selling of stocks.
Congressional efforts to report on the inevitable mess-ups that occur when a computer glitch sends the market plummeting have been an almost comical, as the reports they gather take months to compile while the computers whir on and on.
“In the wake of the flash crash, Mary Schapiro, chair of the Securities and Exchange Commission, publicly mused that humans may need to wrest some control back from the machines. ‘Automated trading systems will follow their coded logic regardless of outcome,” she told a congressional subcommittee, ‘while human involvement likely would have prevented these orders from executing at absurd prices.’
“Delaware senator Ted Kaufman sounded an even louder alarm in September, taking to the Senate floor to declare, ‘Whenever there is a lot of money surging into a risky area, where change in the market is dramatic, where there is no transparency and therefore no effective regulation, we have a prescription for disaster.’”
The comical saga continues even though the SEC tried to get a grip on regulating the insane computers which had displayed their mad ability to disrupt the markets; and, (Gasp!) worse, to bypass regulations altogether. Heaven forefend that any computers bypass by sheer speed of intelligence the regulatory powers of congress and the SEC.
But they did.
The efforts of the SEC and the desire of congress to get a grip on the takeover of machines did little nothing to control the algorithmic market. All their attempts at regulation merely slowed them down or stopped the process for a few minutes.
Salmon and Stokes write, surely with a wry twist of humor, “That’s a tacit admission that the system has outgrown the humans that created it.”
They conclude, “For individual investors, trading with algorithms has been a boon: Today, they can buy and sell stocks much faster, cheaper, and easier than ever before. But from a systemic perspective, the stock market risks spinning out of control. Even if each individual algorithm makes perfect sense, collectively they obey an emergent logic—artificial intelligence, but not artificial human intelligence. It is, simply, alien, operating at the natural scale of silicon, not neurons and synapses. We may be able to slow it down, but we can never contain, control, or comprehend it. It’s the machines’ market now; we just trade in it.”
But perhaps there are even more arresting conclusions to be drawn; namely, that congress, which is a slow moving human institution used to (cough!) slow and methodical deliberation, will remain eternally behind and unable to regulate the momentum of computer technology, not only as it pertains to the national and global markets, but as it pertains to much else as well.
After all, who knows how many unelected Wizards of Oz are behind the innards of the computers that now control the markets of the globe?
In fact, who knows who is in control?