Since I was 22-years-old, I’ve been working with numbers. For all my working life, numbers have served me well. Thanks to them, I was able to earn a living and put food on the table until I retired at age 62. As you already know, I consider myself a “number man”. I firmly believe, that if anything can be measured, it can be managed. Without numbers, it’s almost impossible to manage just about any human endeavor.
With the advent of the digital revolution, numbers acquired a new meaning. Reality as we know it, could be morphed into a digital dimension—ones and zeros. Music, text, videos—you name it—are easily transformed into computer language based on the binary code.
For many years we were elated to work with the binary code and the machines that interpreted it, which we call computers—and lately, tablets. Then the stuff hit the fan in 2008 when we had the global financial meltdown. That year we found out that there was a dark side to numbers. Mathematicians and physicists call it “The Black Box Trading Algorithms”. I’m referring to complex mathematical codes for computers known as algorithms.
In mathematics and computer science, an algorithm is a step-by-step procedure for calculations. Algorithms are used for calculation, data processing, and automated reasoning. Many physicists and mathematicians agree that algorithms create and control our world. These highly complex machine language determine everything from espionage tactics to architecture machine language. They claim that the role of contemporary math and complex algorithms shape our world. That is well and good, but sometimes they show their dark side and destroy everything in sight. On certain occasions, algorithms conflict with each other and are locked in loops creating a kind of havoc nobody seems to understand—not even their creators.
Highly complex algorithms were introduced in Wall Street by computer whiz kids known as “Quants”. The invented a brand new field in the world of finance called “Financial Engineering” based on principles of Math and Physics. In an effort to understand what really caused the Housing Bubble implosion in 2008, pundits and financial experts alike became modern Sherlock Holmes eager to understand and piece together exactly what sank Wall Street. From these investigations a discovery was made which very few people knew about. I’m talking about the Quants, a.k.a The Alchemists of Wall Street. Quants is a term derived from the words “quantitative analysts.”
They are the rocket scientists of finance, highly trained mathematicians, scientists, and engineers who delve deep into quantitative analysis. They created highly complex quantitative models to explain the financial transactions taking place in the real world. These brainy financial engineers cooked up beautiful and elegant formulas that demonstrated which financial instruments had the highest probability of generating the highest return at the lowest risk, and Wall Street rolled with them—though, as we’ve learned, those formulas sometimes work better on paper than they do in real life. The quants’ perspective was somewhat different, they defined their software as a “delicate, intricate web of logic.” We all know it was only air.
Even after the horror of the economic crisis of 2008, quants is a growing ideology even as we speak. This reduced group of financial technologists firmly believe they can beat the market with their elegant non-linearity concepts—”Throw some epsilons and thetas on a paper, hoist a few PhDs behind your name, and now you’re an expert in divining the future.”
Another example of algorithms gone completely haywire is known as The Flash Crash of May 6, 2010 (or “The Crash of 2:45”!). On this unfortunate moment in time, the Dow Jones plunged a 1000 points and then gained a 1000—all in a few instants. Nine percent of the entire market disappeared from the computer screen for five minutes. Nobody had the slightest idea what was going one. There are speculations that high speed automated trading based on complex computer algorithms caused the entire United States system to seize.
“Over the past decade, trading in financial markets has undergone a technological revolution. The frontier of this revolution is defined by speed. A decade ago, trade execution times were measured in seconds. A few years ago, they were measured in milliseconds. Today, they are measured in microseconds. Tomorrow, it will be nano-seconds or pico-seconds”.
According to Kevin Slavin, a well-known mathematician, “It takes you 500,000 microseconds just to click a mouse. But if you’re a Wall Street algorithm and you’re five microseconds behind, you’re a loser.”
Wall Street is speaking a new language difficult for humans to understand and control. The new technological terms are “quote stuffing”, “zero latency” and “message traffic congestion”. As the terms become more technical, more silicon—it becomes clear that human control over trading, as over language, is dwindling. (Rather, technology is molding language). The great threat of a market crash engendered by computer trading is become more likely. And with that something, more disturbing evolved from this fact—the realization that none of this market making is actually real any more—it can’t be when trades are happening in “pico-seconds”. It all takes place in a silicon space.
We are in a new world that does not recognizes the blind watch maker and does not obey Darwinian rules. That like, The Terminator, just keeps coming on, in trades “faster than the speed of light”.
Algorithms have shaped the world into a surrealistic painting similar to “The Persistence of Memory” painted by Salvador Dalí in 1931, which depicts lifeless hanging clocks from limbs of trees and walls. Reality is now distorted by a computer language we no longer recognize, and even less, control.
The following video dubbed, “How Algorithms Shape Our World” created by Kevin Slavin explains the mysterious world of numbers and its scary consequences. Put on your thinking caps and concentrate on the words of Mr. Slavin. Numbers will have a different meaning from this day on.
Question: Why is a raven like a writing desk?
Answer: Because the bankers told the regulators that it was.
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