Math geniuses replace traders on Wall Street
Software programs rule the roost
LONDON — Stock market traders are being replaced by math geniuses who use super-computers to beat the markets.
At seven minutes past one on the afternoon of Tuesday April 23 this year, a tweet from the AP news agency in Washington was published. “Breaking: Two Explosions in the White House and Barack Obama is injured.” This was not true — the AP account had been hacked by a shady group of technology nerds calling themselves The Syrian Electronic Army — but within milliseconds the tweet had been noticed and flagged by trading computers on Wall Street.
Programmed to scan the Internet for words or phrases that might affect stock markets, the unthinking machines had immediately seized upon the tweet, noted the proximity of the words “Obama,” “explosions” and “White House” and unleashed a torrent of trades. With in seconds, the Dow Jones had plunged 140 points and more than $200 billion US of capital had been wiped out.
A few minutes later the report was exposed as a hoax and the markets quickly returned to their pre-tweet levels. But, to many, the idea that one fake tweet could have such an enormous impact on the financial markets was incredible. Who was running Wall Street? Humans or machines?
If you thought “humans,” you were woefully out of date. Over the past decade or so there has been a technological coup d’etat on the trading floor. The old “Masters of the Universe” — the Gordon Gekko types with their slicked-back hair and $5,000 suits — have been superseded by unbelievably powerful computers capable of analyzing vast amounts of data and buying or selling shares in the blink of an eye.
Today, if you visit a trading floor, instead of pumped-up men in loose ties screaming down the phone, you are more likely to see rows of studious– looking people (most of them still men) sitting in front of computer screens, quietly monitoring trades being carried out on their behalf by machines.
Around 70 per cent of the orders to buy or sell on Wall Street are now placed by software programs, and the studious-looking people, mathematical geniuses who are responsible for writing these programs, are the new “smartest guys in the room.” It is the age of the algorithm.
Mathematicians made their first forays into the financial world in the late ’60s. Edward Thorp, a professor of mathematics at the University of California, published a book in 1967 called Beat the Market in which he laid out what he claimed was a foolproof way of making money on the stock market, all based on a system he had previously devised to beat casinos at blackjack. The blackjack system had been so successful it had forced casinos to change their rules and Beat the Market — advising on selling stocks and bonds at one price and buying them back at a lower price — proved to be even more groundbreaking. In 1974, Thorp founded a hedge fund called Princeton/ Newport Partners and proceeded to make a killing on the markets.
At the same time, the job prospects for scientists had nosedived. Since the 1969 moon landing, the American government had cut funding for science programs and diverted it to the war in Vietnam.
“A generation of physicists who had gone to graduate school left with their PhDs and entered a severely depressed job market,” explains James Owen Weatherall, author of The Physics of Finance. They had to earn a living somehow, and, seeing how much money that there was to be made on Wall Street, many decided to move into finance.
In Britain, the fall of the Soviet Union led to an influx of Warsaw Pact scientists. In both cases, these scientists brought with them a new methodology based on analyzing data and also a faith that, using sufficient computing firepower, it was possible to predict the market. It was the start of a new discipline, quantitative analysis, and the most famous “quant” of all was a shambling donnish math genius with a scraggly beard and aversion to socks called Jim Simons.
For those who know their physics, Simons is a living legend. A piece of mathematics he co-created, the Chern- Simons 3-form, is one of the most important elements of string theory, the so-called “theory of everything. Highly academic, Simons never seemed the sort of person who would gravitate to the earthy environs of Wall Street. But in 1982, he founded an extraordinarily successful hedge fund management company, Renaissance Technologies, whose signature fund, Medallion, went on to earn an incredible 2,478.6 per cent return in its first 10 years, way above every other hedge fund on the planet, including George Soros’s Quantum Fund.
Its success, based on a highly complex and secretive algorithm, continued into the current millennium and over the lifetime of the fund, Medallion’s returns have averaged 40 per cent a year, making Simons one of the richest men in the world with a net worth in excess of $10 billion US.
Of his 200 employees, ensconced in a fortress-like building in unfashionable Long Island, New York, a third have PhDs, not in finance, but in fields like physics, mathematics and statistics. Renaissance has been called “the best physics and mathematics department in the world” and, according to Weatherall, “avoids hiring anyone with even the slightest whiff of Wall Street bona fides. PhDs in finance need not apply; nor should traders who got their start at traditional investment banks or even other hedge funds. The secret to Simons’s success has been steering clear of the financial experts.”
Not surprisingly, old-style traders hate the quants. Not only have they pushed them off the top of the trading tree, there is also a basic clash of cultures. They are not flash and, invariably, rather awkward socially.
In this game speed is critical and that has led to what has been dubbed an arms race between firms. It has got to a point where firms have actually started moving their servers nearer to an exchange to speed up connection times.