The Quants; Scott Patterson

Newton observed: “I can calculate the motion of heavenly bodies but not the madness of people.”

The quants created a name for the Truth, a name that smacked of cabalistic studies of magical formulas: alpha. It is used in contrast with another Greek term, beta , which is shorthand for plain-vanilla market returns anyone with half a brain can achieve. Asness named his first hedge fund, hatched inside Goldman in the mid-1990s, Global Alpha. Before moving on to Morgan in 1992, Muller had helped construct a computerized investing system called Alphabuilder.

A wearable computer that could track the motion of ball and wheel and spit out a prediction of where it would land.

A reporter asked a casino owner whether gambling ever paid off. “When a lamb goes to the slaughter, the lamb might kill the butcher,” the owner said. “But we always bet on the butcher.”

A key part of the answer, Thorp discovered, was found in a book he’d picked up after he’d switched his attention from blackjack to Wall Street. It was called The Random Character of Stock Market Prices. That meant the future direction of the market as a whole, or any individual stock or bond, was a coin flip: there was a 50–50 chance that it could rise or fall. That was completely and mysteriously random. (The mystery remained unsolved for decades, until Albert Einstein, in 1905, discovered that the strange movement, by then known as Brownian motion, was the result of millions of microscopic particles buzzing around in a frantic dance of energy.)

The connection between Brownian motion and market prices was made in 1900 by a student at the University of Paris named Louis Bachelier. That year, he’d written a dissertation called “The Theory of Speculation”. This discovery came to be called the random walk . It’s also called the drunkard’s walk. Visually, a chart of the various outcomes of a random walk is known as a bell curve. (the more observations, the more coin flips, the greater the certainty of prediction). Using their models and their ability to predict volatility, Thorp and Kassouf realized there were a number of warrants that appeared to be mispriced. Some were too expensive, while others were cheap. The two professors collaborated on a 1967 book that described their findings. It was called Beat the Market: A Scientific Stock Market System . Using their models and their ability to predict volatility, Thorp and Kassouf realized there were a number of warrants that appeared to be mispriced. Some were too expensive, while others were cheap. The two professors collaborated on a 1967 book that described their findings. It was called Beat the Market: A Scientific Stock Market System .

The physical world, he said, is “Mediocristan.” Bell curves are perfect for measuring the heights or weights of people. If you measure the height of a thousand people, the next measurement isn’t likely to change the average. In finance, however, a sudden swing in prices can change everything. This is Taleb’s world of “Extremistan.”

Like Thorp, Griffin quickly discovered that a number of convertible bonds were mispriced. His computer skills came into play as he wrote a software program to flag mispriced bonds.

Tartaglia… renamed the group he’d taken over Automated Proprietary Trading, or APT, which was soon trading so much that at times it accounted for 5 percent of the daily trading volume on the NYSE. By 1989, APT had started to lose money. Eventually he was forced out. Shortly after, APT itself was shut down.

Shaw landed on his feet, starting up his own investment firm with $28 million in capital and naming his fund D. E. Shaw. It soon became one of the most successful hedge funds in the world. Its core strategy: statistical arbitrage.

Like Thorp, Griffin quickly discovered that a number of convertible bonds were mispriced. His computer skills came into play as he wrote a software program to flag mispriced bonds.

These are mathematical models. We look at statistics, historical data, trends, and extrapolate what we can from them. This isn’t physics. In physics, you can build the space shuttle, launch it into orbit, and watch it land at Cape Canaveral a week later. The market is far more unstable and unpredictable. What we know about it are approximations about reality based on models.

By 1969, Fama distilled the collected ideas of this class, and years of computerized number crunching, into the first fully formed articulation of a cornerstone of modern portfolio theory: the efficient-market

EMH gave the quants a touchstone for what the market should look like if it were perfectly efficient, constantly gravitating toward equilibrium. In other words, it gave them a reflection of the Truth, the holy grail of quantitative finance, explaining how the market worked and how to measure it. Every time prices in the market deviated from the Truth, computerized quant piranhas would detect the error, swoop in, and restore order—collecting

In the financial planning community, so-called Monte Carlo simulations, which can forecast everyday investors’ portfolio growth over time, used the idea that the market moves according to a random walk.

Renaissance Technologies, the most secretive hedge fund in the world, founded by a man who once worked as a code breaker for the U.S. government. Its returns, at roughly 40 percent a year over the course of three decades, are by a wide margin unmatched in the investing world. Warren Buffett’s storied Berkshire Hathaway averaged an annual return of about 20 percent. (Of course, scale matters: Medallion has about $5 billion in capital, while Berkshire is worth about $150 billion, give or take a few billion.)

By April 1989, it had dropped nearly 30 percent. Alarmed by the shift in fortunes, Simons ordered Ax to stop trading. Ax resisted, convinced he could turn things around.

A crucial change was a shift to higher-frequency trading. Typically, the fund would hold on to positions for several days, even weeks. Berlekamp and Simons decided to shorten average holding periods to less than a day, or even just an hour, depending on how far a position moved. From a statistical point of view, they realized, the ability to predict what will happen tomorrow, or in the next few hours, is far better than the ability to predict what will happen a week or two down the road. The goal was to make a lot of bets, as many as possible, just as long as there was also a slight statistical edge.
Simons closed the fund to new investors in 1993 with $280 million in assets. In 1994, returns hit an eye-popping 71 percent. The fund’s success became so reliable that its researchers and traders (all sporting Ph.D.’s) forgot what it was like to lose. When Medallion posted a rare 0.5 percent loss in a single quarter of 1999, at least one employee actually wept.

Ax, Berlekamp, and of course Simons himself. Cryptographers are trained to detect hidden messages in seemingly random strings of codes.

Renaissance has a concept known as the “second forty hours.” Employees are each allotted forty hours to work on their assigned duties—programming, researching markets, building out the computer system. Then, during the second forty hours, they’re allowed to venture into nearly any area of the fund and experiment. Renaissance was also free of the theoretical baggage of modern portfolio theory or the efficient-market hypothesis or CAPM. Rather, the fund was run like a machine, a scientific experiment, and the only thing that mattered was whether a strategy worked or not—whether it made money.

later in the year Simons retired as CEO of Renaissance, replaced by the former IBM voice recognition gurus Peter Brown and Robert Mercer.

Ken Griffin was swapping convertible bonds from a high tower in Chicago. Jim Simons was building his quant empire in East Setauket. Boaz Weinstein was scouring computer screens to trade derivatives for Deutsche Bank. Peter Muller was trading stocks at Morgan Stanley. Cliff Asness was measuring value and momentum at AQR.

August 3, 1998, AQR was up and running with $1 billion in start-up capital—one of the largest hedge fund launches on record at that point,

a little-known group of physicists and scientists running a cutting-edge computerized trading outfit from a small building in Santa Fe, New Mexico. They called themselves Prediction Company. A founder of Prediction Company was Doyne Farmer, a tall, ropy physicist and early innovator in an obscure science called chaos theory. Given more to tie-dyed T-shirts and flip-flops than the standard-issue Wall Street suit and tie, Farmer had followed in Ed Thorp’s footsteps in the 1980s, creating a system to predict roulette using cutting-edge computers wedged into elaborate “magic” shoes. Also like Thorp, Farmer moved on from gambling in casinos to making money using mathematics and computers in financial markets

Muller made a mental note: Stay calm, look cool, be confident .

PDT’s dream team built an automatic trading machine, a robot for making money. They called their robot Midas. If four airline companies were going up and three were going down, Midas would short the stocks going up and buy the stocks going down.

humans are flawed; it’s best to let the computer run the show.

After hitting the blackjack tables, where Weinstein won over and over again using the card-counting techniques he’d learned from Beat the Dealer.

gambling was just a pastime, a mental curiosity or warm-up for the real deal.

His signature trade was a strategy called “capital structure arbitrage,” based on gaps in pricing between various securities of a single company. For instance, if he thought its bonds were undervalued relative to its stock, he might take bullish positions on the bonds and simultaneously bet against the stock, waiting for the disparity to shrink or vanish. Weinstein was looking for inefficiencies in firms’ capital structures, their blend of debt and stock, and used credit default swaps in creative ways to arb the inefficiencies.

Muller was living a life few people could imagine. With little need to work as his quant machine cranked out profits in New York, he was free to travel the world. At the same time, he was working on an album of songs. A press release about the album says: “Pete Muller woke up more than 6 years ago and realized that he could no longer find happiness in the corporate world. While he felt accomplished and satisfied, he couldn’t find a new challenge, a goal to aspire to, and turned his attention wholly to his music.”

He began to disappear from the office for weeks at a time, then months, only to pop up one day with a sweeping critique of PDT’s operations before vanishing again just as abruptly. One PDT trader labeled it seagull management: swoop by every now and then, shit all over everything, and fly away. Around 2000, Shakil Ahmed took over the reins. Muller became a paid advisor, though he remained a partner at Morgan. He traveled the world, visiting the most exotic locales he could find: Bhutan, New Zealand, Hawaii. Muller, meanwhile, was getting restless. Playing endless rounds of poker, hiking exotic trails in Hawaii, kayaking in Peru, shooting off on private jets to the Caribbean.

It had put up just single-digit gains in 2006 as a flood of copycats could deliver. Back at Morgan, Muller was on top again at his old trading outfit. He had bold plans to expand the operation and increase its profits. Part of his plans included juicing returns by taking on bigger positions.

Weinstein reveled in his success. Now a wealthy playboy, every summer he would rent a different vacation home in the Hamptons. He continued to gamble, playing high-stakes games alongside celebrities such as Matt Damon.

One reason why banks engage in securitization is to spread around risk like jelly on toast. Instead of lumping the jelly on one small piece of the toast, leaving all the reward (or risk that it falls off the toast) for one bite, it’s evenly distributed, making for lots more tasty bites—and, through the quant magic of diversification (spreading the jelly), less risk.

the same mathematical trick Ed Thorp used to beat blackjack in the 1960s and that Black and Scholes used to price options.

Morgan was borrowing $32 for every $1 it actually owned. Other investment banks, such as Bear Stearns, Lehman Brothers, and Goldman Sachs, also had sky-high banks showed the leverage was even higher than the official numbers reported to the SEC. There were all kinds of deals we were doing that only made sense if credit is good. We knew at some point that the musical chairs would stop.

That was a problem. The Ph.D.’s might know their sines from their cosines, but they often had little idea how to distinguish the fundamental realities behind why the market behaved as it did. They got bogged down in the fine-grained details of their whiz-bang models.

Physics, because of its astonishing success at predicting the future behavior of material objects from their present state, has inspired most financial modeling. Physicists study the world by repeating the same experiments over and over again to discover forces and their almost magical mathematical laws. … It’s a different story with finance and economics, which are concerned with the mental world of monetary value. The truth is that there are no fundamental laws in finance. In other words, there is no single truth in the chaotic world of finance, where panics, manias, and chaotic crowd behavior can overwhelm all expectations of rationality.

As Gross and Thorp sat together in Pimco’s conference room, they got to musing about the Kelly criterion, the risk management strategy Thorp used starting with his blackjack days in the 1960s. Pimco, Gross noted, uses a version of Kelly.

- Edward O. Thorp: Princeton/Newport Partners; “Beat the Dealer", "A Man for All Markets: From Las Vegas to Wall Street, How I Beat the Dealer and the Market"; "A Winning Strategy for Blackjack”
- Peter Muller: Morgan Stanley
- Ken Griffin: Chicago's Citadel LLC
- James Simons: Renaissance Technologies
- Clifford S. Asness and Aaron Brown: AQR Capital Management 
- Boaz Weinstein: Deutsche Bank

- Markowitz’s
- William Sharpe, who eventually won the Nobel Prize for economics 
- Credit default swaps trading: Created in the early 1990s, these contracts essentially provide insurance on a bond or a bundle of bonds. The price of the insurance fluctuates depending on the riskiness of the bonds. In the late 1990s and 2000s, more and more traders used the contracts to make bets on whether a bond would default or not. At Deutsche Bank, Boaz Weinstein was a pioneer in the use of CDS as a betting instrument.
- “The Use, Misuse and Abuse of Mathematics in Finance,” published in 2000 in Philosophical Transactions of the Royal Society