The Quants: The maths geniuses who brought down Wall Street

by Scott Patterson

They could short the overpriced warrants and buy an equivalent chunk of stock to hedge their bet. If the stock started to rise unexpectedly, their downside would be covered by the stock. The formula also gave them a method to calculate how much stock they needed to hold in order to hedge their position. In the best of all worlds, the warrant price would decline and the stock would rise, closing out the inefficiency and providing a gain on each side of the trade. This strategy came to be known as convertible bond arbitrage. It has become one of the most successful and lucrative trading strategies ever devised, helping launch thousands of hedge funds, including Citadel Investment Group, the mammoth Chicago powerhouse run by Ken Griffin.

Shaw’s presentation on parallel processing and high-speed algorithms was proceeding normally. Suddenly, he started to expound on complex mathematical bond-arbitrage strategies. As the meeting ended, APT’s traders and researchers sat fuming in their chairs. Shaw had crossed the line. Programmers weren’t supposed to trade, or even think about trading. Back then, the line between programmer and trading strategist remained firmly in place, a boundary that steadily dissolved as trading became more and more computerized.

“There do seem to be a few outliers that are impossible to explain. In every science there are freaks that seem to defy all the rules. Buffett, as well as Peter Lynch at Fidelity’s Magellan fund, have had consistent returns over the years. I’m not aware of anyone else. These freak geniuses may be out there, but I don’t know who they are. Who knows,” he said with a shrug and a smile, “maybe they’ll lose it all next year.”

Imagine a neighborhood that enjoys two kinds of pizza—pepperoni and mushroom. For a time both pizzas are equally popular. But suddenly mushroom pizzas fall out of favor. More and more people are ordering pepperoni. The pizza man, noticing the change, boosts the price for his pepperoni pizzas and, hoping to encourage more people to buy his unloved mushroom pies, lowers the price. The price disparity eventually grows so wide that more people gravitate toward mushroom, leaving pepperoni behind. Eventually, mushroom pizzas start to gain in price, and pepperonis decline—just as Fama and French predicted.

Of course, it’s not always so simple. Sometimes the quality of the mushrooms are on the decline and the neighborhood has a good reason for disliking them, or the flavor of the pepperoni has suddenly improved. But the analysis showed that, according to the law of large numbers, over time value stocks (unloved mushrooms) tend to perform better than growth stocks (pricey pepperoni).

Fama and French also found that small stocks tended to fare better than large stocks. The notion is similar to the value and growth disparity, because a small stock is intuitively unloved—that’s why it’s small. Large stocks, meanwhile, often suffer from too much love, like a ...

A trader who purchased a swap on GM for $1 million could potentially sell the swap to another trader later on for, say, $2 million, simply on the perception that GM’s fate had worsened. At the end of the day, it was all very simple: traders were betting on a level, just like a stock. If the company looked shaky, the CDS cost would rise. In theory, hundreds of swaps, or more, can be written on a single bond. More commonly, swaps are written on baskets of hundreds or thousands of bonds and on other kinds of loans. They could metastasize without end—and did—reaching a value of more than $60 trillion a decade after Weinstein arrived on the scene.

The result was a model they called value-at-risk, or VAR. It was a metric showing the amount of money the bank could lose over a twenty-four-hour period within a 95 percent probability.

LTCM had relied on complex hedging strategies, massive hairballs of derivatives, and risk management tools such as VAR to allow it to leverage up to the maximum amount possible. By carefully hedging its holdings, LTCM could reduce its capital, otherwise known as equity. That freed up cash to make other bets.

In March 2000, when the dot-com bubble began to implode, reversing trends in technology stocks that had been in place for several years, Medallion lost $250 million

in three days, nearly wiping out its year-to-date profit. But the fund quickly bounced back and put up another year of stellar returns.

At first blush, speech recognition and investing would appear to have little in common. But beneath the surface, there are striking connections. Computer models designed to map human speech depend on historical data that mimic acoustic signals. To operate most efficiently, speech recognition programs monitor the signals and, based on probability functions, try to guess what sound is coming next. The programs constantly make such guesses to keep up with the speaker.

Volfbeyn accused Renaissance of asking him to devise methods to “defraud investors trading through the Portfolio System for Institutional Trading, or POSIT,” referring to a dark pool of liquidity—essentially an electronic market that matches buy and sell orders for stocks out of the public eye. Volfbeyn said he was instructed to create a code that would “reveal information that POSIT intended to keep confidential,” according to an article by Bloomberg, and that he refused to participate in the scheme, as well as others, because he believed they were against the law. The suit also hinted at a nefarious swaps deal that he described as a “massive scam,” but didn’t explain the deal in detail.

Michael Bloomberg, a former stock trader at Salomon Brothers and eventual mayor of New York City, designed a machine that would allow users to get data on virtually any security in the world in seconds, turning its creator into a billionaire. The Nasdaq Stock Market, which provided entirely electronic transactions, as opposed to the lumbering humans at the New York Stock Exchange, made it quicker and cheaper to buy and sell stocks around the globe. The entire global financial system became synced into a push-button electronic matrix of unfathomable complexity. Money turned digital.

The fund, like Princeton/Newport Partners, specialized in using mathematical models to discover deals in the opaque market for convertible bonds.

“merger arbitrage” group that made bets on the shares of companies in merger deals.

At Deutsche Bank, risk wasn’t fucking managed. Risk was bitch-slapped, risk was tamed and told what to do.

“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. If his long position on the debt fell through, he’d be compensated on the other side of the trade when the stock collapsed.

Private equity firms are akin to hedge funds in that they are largely unregulated and cater to wealthy investors and large institutions. They wield war chests of cash raised from deep-pocketed investors to take over stumbling companies, which they revamp, strip down, and sell back to the public for a tidy profit.

A bank account in Japan would yield about half a percent a year, compared with about 5 percent in the United States or 10 percent or more in some other countries. This dynamic meant firms with the know-how and financial dexterity could borrow yen in Japan—practically for free—and invest it in other assets with higher interest rates, such as bonds, commodities, or other currencies. And the extra cash that kicked out could be deployed into even more investments, such as commodities or subprime mortgages. Add a healthy dose of leverage, and you have a perfect recipe for a worldwide speculative binge.