The Quants Part 10

Weinstein tried to tone down the group's overtly nerdy side and often claimed that he wasn't really really a quant, downplaying the complexity of his trades. His emails contained the quip "It's not rocket surgery," deliberately conflating the cliches of the rocket scientist quant practicing brain surgery with complex derivatives. a quant, downplaying the complexity of his trades. His emails contained the quip "It's not rocket surgery," deliberately conflating the cliches of the rocket scientist quant practicing brain surgery with complex derivatives.

Quants were too careful, too worried about risk management; they had no feel for the market. No risk, no reward. But an aggressive approach holds its dangers. Deutsche Bank had its own cautionary tale in the person of Brian Hunter, who'd worked on Deutsche's energy desk before moving on to Amaranth. Hunter had generated millions of dollars for the bank trading natural gas in the early 2000s, until losing $51 million in a single week in 2003. Hunter blamed Deutsche's faulty software. Deutsche blamed Hunter, and the two parted ways.

Some worried that Weinstein was getting in over his head. He also helped run Deutsche Bank's U.S. "flow" desk, which facilitated trades with clients such as hedge funds or the bond giant Pimco. The job put Weinstein atop the so-called Chinese wall that separates a bank's trading operations from its client-facing side. There were never any allegations that Weinstein abused his position. But the fact that Deutsche Bank gave Weinstein such power was testimony to its desperation to keep him at the switch, pulling in hundreds of millions in profits. The high-stakes race for profits was transforming once-staid banks into hot-rod hedge funds fueled by leverage, derivatives, and young traders willing to risk it all to make their fortunes. Weinstein was at the center of the s.h.i.+ft.

He didn't let Deutsche down. Weinstein and his prop desk gun-slingers continued to ring the cash register. The prop group pulled in $900 million in 2006, earning Weinstein a paycheck of about $30 million.

Most of his attention was focused on his prop desk, however, alienating his underlings on flow, who didn't think they were getting enough recognition. In 2005, he'd hired Derek Smith, a star trader at Goldman Sachs, to run the flow desk, angering a number of traders who felt they deserved to run the show. The number of Weinstein's enemies within Deutsche started to grow.

"Why do we need an outsider?" they grumbled.

Weinstein's monetary incentives were skewed heavily toward the prop desk side. While his compensation for his flow desk job was a discretionary bonus, his prop desk business rewarded him with a healthy percentage of the profits.

There was a good reason for Weinstein's tunnel vision: his eyes were squarely focused on launching his own hedge fund in the next few years following the tradition set by Cliff Asness years ago when he'd broken away from Goldman Sachs to launch AQR. In early 2007, Weinstein renamed his prop-trading group Saba. It encompa.s.sed about sixty people working in offices in New York, London, and Hong Kong.

The name would brand the group on the Street, making it immediately recognizable once it broke away from Deutsche Bank. Saba was increasingly known and feared as a major force with ma.s.sive financial ammunition, a major player nearing the level of bond-trading powerhouses such as Citadel and Goldman Sachs.

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.

He also continued to gamble with his fellow quants in New York. The game, of course, was poker.

Boaz Weinstein dealt crisply, talking a blue streak. There was no smoke in the room as the cards fell about the table. Peter Muller, the compulsive health nut who nearly pa.s.sed on the BARRA job due to his discovery of a single cigarette b.u.t.t in the company's bathroom, didn't allow smoking Muller's rule didn't bother the quants. Neither Cliff Asness nor Weinstein smoked. But every now and then, a seasoned poker professional who couldn't fathom the notion of poker separated from an endless chain of cigarettes would sit in on the quants' game and be forced to clock an excruciating night of nicotine-free, high-stakes gambling. dealt crisply, talking a blue streak. There was no smoke in the room as the cards fell about the table. Peter Muller, the compulsive health nut who nearly pa.s.sed on the BARRA job due to his discovery of a single cigarette b.u.t.t in the company's bathroom, didn't allow smoking Muller's rule didn't bother the quants. Neither Cliff Asness nor Weinstein smoked. But every now and then, a seasoned poker professional who couldn't fathom the notion of poker separated from an endless chain of cigarettes would sit in on the quants' game and be forced to clock an excruciating night of nicotine-free, high-stakes gambling.

On this particular night in late 2006, it was just the quants going head-to-head. Weinstein was regaling the table with tales of "correlation," a technical term from credit trading that he was explaining in detail to his poker buddies.

"The a.s.sumptions are crazy," he said, placing the deck on the table and picking up his hand. "The correlations are ridiculous."

It all had to do with the explosion in housing prices. The housing market had been booming for years and looked to be losing steam in overheated regions such as southern California and Florida. Home prices had more than doubled nationwide in a matter of five years, helping prop up the economy but leading to an unsustainable bubble. A growing number of investors, including Weinstein, thought it was about to pop like an infected boil.

Weinstein had a unique view into Wall Street's end of the bubble. Deutsche Bank was heavily involved in mortgage lending-some of it on the subprime side. In 2006, it had purchased Chapel Funding, a mortgage originator, and had teamed up with the Hispanic National Mortgage a.s.sociation to make loans to Hispanic and immigrant borrowers.

Deutsche Bank was also a big player in the securitization market, buying mortgage loans from lenders, packaging those loans into securities, then slicing and dicing them into different pieces to peddle to investors around the world.

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.

If an investor buys a single subprime mortgage worth $250,000, that investor bears the entire risk if that mortgage goes into default, certainly possible given the fact that subprime mortgages usually go to the least creditworthy borrowers. But if a thousand subprime mortgages, each worth about $250,000, were pooled together and turned into a single security with a collective value of $250 million, the security could be divided into some number of shares. The potential loss caused by any one mortgage going into default would be offset by the fact that it represented only a tiny portion of the security's total value.

Parts of the securities, in many cases the lowest on the food chain, were often bundled into even more esoteric monstrosities known as collateralized debt obligations, which took into account the fact that some of the underlying mortgages were more likely than others to default. The more-likely-to-default bundles obviously carried greater risk, though along with that came its corollary, greater potential reward. Between 2004 and 2007, billions in subprime home loans were stuffed into these so-called CDOs. The CDOs were then sliced into tranches. There were high-quality slices, stamped AAA by rating agencies such as Standard & Poor's, and there were poor-quality slices, some of which were so low in quality they didn't even get a rating.

Bizarrely, the ratings weren't based on the relative quality of the underlying loans. The AAA tranches could hold loans of the same value and quality as those in the lowest-rated tranches. The ratings, rather, were based on who got paid first in the stack of loans. The owners of AAA tranches had the first dibs on payments. When borrowers started to default, the owners of the lowest-tier tranches got whacked first. If enough borrowers defaulted, higher-rated tranches would start to suffer.

One of the problems with the Byzantine practice of carving up CDOs into all of these slices was figuring out how to price them. Sometime around 2000, the quants came up with an answer: correlation. By getting the price of one small part of the bundle of slices, quants could figure out the "right" prices of all the other slices by looking at how correlated they were with one another. If the pool of loans started experiencing, say, a 5 percent rate of defaults, the quants could calculate the impact on each of the slices through their computers and figure out the correlations between each slice of the pie, all the way up to the AAA slice.

It was a.s.sumed, of course, that the poor-quality slices and the AAA slices had very little in common in terms of the likelihood of defaults by the homeowners who received the original mortgages. Put another way, the correlation between them was extremely low, almost infinitesimal.

Weinstein and several other traders at Deutsche Bank (and a number of clever hedge funds) figured out that the correlations in most models were off by miles. When they peered into the underlying loans in the CDOs, they discovered that many of the loans were so shaky, and so similar, that when one slice of the pie started to go bad, that meant the entire pie would be rotten. So many low-quality loans had been stuffed into the CDOs that even owners of seemingly safe, high-rated tranches would suffer. In other words, the correlations were very high high. But most people buying and selling the slices thought they were very low low.

To Weinstein, that meant a trade. Through even more esoteric quant alchemy, there were ways to "short" CDO slices through Weinstein's favorite method: credit default swaps. By purchasing a swap, or a bunch of swaps bundled together, Weinstein would effectively take out an insurance policy on the underlying subprime loans. If those loans went belly up-which Weinstein thought most likely-the policy paid out. In simple terms, Weinstein was betting that the market was underestimating the toxicity of the subprime mortgage market.

Even better for Weinstein, most traders were so enthusiastic about the housing market and the CDOs bundling all those loans that the cost of shorting the market was extremely cheap. Weinstein saw this as an almost can't-lose bet. Huge profits could be made. And if he was wrong, he'd lose only the scant amount he'd paid for the insurance policy.

"We're putting on the trade at Deutsche," Weinstein said, gazing at his cards.

Asness and Muller nodded. It was typical quant shoptalk, one trader describing a clever new bet to his peers, but they were getting bored. It was time to get down to the business at hand. The only bet on their minds at the moment involved a pile of chips worth several thousand dollars in the center of the table.

Weinstein looked at his hand and grimaced. He had nothing and folded.

"Raise a thousand," Asness said, tossing more chips on the pile.

Muller peered at Asness, who sat back in his chair and grinned nervously, his face reddening. Poor Cliff. It's so easy to tell when he's bluffing. No poker face whatsoever on the man Poor Cliff. It's so easy to tell when he's bluffing. No poker face whatsoever on the man.

"Call," Muller said, throwing down another winning hand to Asness's agonized groan. Muller was on a hot streak, and he laughed as he swept the chips into the steadily rising pile in front of him.

"I KEEP MY FINGERS CROSSED FOR THE FUTURE"

Boaz Weinstein wasn't the only one worrying about the health of CDOs in 2007. Aaron Brown-the quant who'd beaten Liar's Poker in the 1980s-had gotten his hands dirty in the securitization industry almost since its inception. His career had provided him with a front-row seat on its evolution and cancerous growth throughout Wall Street. For years he had watched with increasing trepidation as the CDO industry grew larger and, at the same time, more divorced from reality. By 2007, Brown was working at Morgan Stanley as a risk manager and growing uncomfortable with Morgan's subprime exposure. He was ready to get out. wasn't the only one worrying about the health of CDOs in 2007. Aaron Brown-the quant who'd beaten Liar's Poker in the 1980s-had gotten his hands dirty in the securitization industry almost since its inception. His career had provided him with a front-row seat on its evolution and cancerous growth throughout Wall Street. For years he had watched with increasing trepidation as the CDO industry grew larger and, at the same time, more divorced from reality. By 2007, Brown was working at Morgan Stanley as a risk manager and growing uncomfortable with Morgan's subprime exposure. He was ready to get out.

He'd already been in low-level discussions about a job with a hedge fund that was staffing up for an IPO: AQR. Cliff Asness's firm was looking for a risk management veteran to deal with th.o.r.n.y issues such as international risk regulations. Brown loved the idea. He'd never worked at a hedge fund and was eager to give it a shot. In June 2007, he signed on as AQR's chief risk officer.

Brown was well aware of AQR's reputation as a top-of-the-line quant shop that spoke his language. But he had little idea that AQR, like Morgan Stanley, was sitting on top of a bubbling cauldron of risk that was about to explode in spectacular fas.h.i.+on.

Growing up in Seattle, Brown had always been fascinated by numbers-baseball box scores, weather charts, stock pages. He couldn't have cared less about the events they denoted-the walk-off home runs, the hurricane-wrecked trailer parks, the mergers of corporate rivals. It was the rows of digits that caught Brown's fancy, the idea that there was some kind of secret knowledge behind the numbers. His love of mathematics eventually led him to one of the most influential books he would ever read: Ed Thorp's in Seattle, Brown had always been fascinated by numbers-baseball box scores, weather charts, stock pages. He couldn't have cared less about the events they denoted-the walk-off home runs, the hurricane-wrecked trailer parks, the mergers of corporate rivals. It was the rows of digits that caught Brown's fancy, the idea that there was some kind of secret knowledge behind the numbers. His love of mathematics eventually led him to one of the most influential books he would ever read: Ed Thorp's Beat the Dealer Beat the Dealer.

Brown devoured the book, mesmerized by the idea that he could use math to make money at a game as simple as blackjack. After mastering Thorp's card-counting method, he moved on to poker. At fourteen, he became a regular in Seattle's underground gambling halls. Seattle was a port town full of sailors, hard-luck transients, and been-around-the-world sharpies. Brown couldn't match them for machismo, but they couldn't touch his math or his intuition. He quickly realized that he was very good; he excelled not just at figuring the odds of each hand but at reading the poker faces of his opponents. He could sense a bluff a mile away.

In 1974, he graduated from high school with top grades, got perfect scores on his college board exams, and headed straight for Harvard. He studied under Harrison White, a sociologist who applied quant.i.tative models to social networks, and also dove into Harvard's active poker scene, which included George W. Bush as a regular in Harvard Business School's poker circles. Indeed, Harvard's b.u.mper crop of spoiled rich kids seemed eager to lose money to Brown, and he was happy to oblige. But the stakes were usually too low for his taste, or the games too unprofessional. He made his way to a game future Microsoft founder Bill Gates ran at Harvard's Currier House, but Brown found it too regimented and uptight. A bunch of tense nerds trying to act cool, he thought.

After graduating in 1978, Brown took a job at American Management Systems, a consulting firm in northern Virginia. The job was fine, but the D.C. poker circuit was a bigger draw. It was no trouble to get in on games with the odd congressman. Once he heard about a party that had a hot backroom game. He walked into an apartment and saw a heavyset man wearing a tight T-s.h.i.+rt, girls who looked like dolled-up secretaries hanging from each arm. It was none other than Texas congressman Charlie Wilson, future subject of the book and movie Charlie Wilson's War Charlie Wilson's War. Brown liked Wilson, thought he was a fun guy. Better yet, Wilson loved to play poker. He wasn't bad at it, either.

Brown wasn't satisfied with his job, though, and once again felt the tug of academia. In 1980, he started taking cla.s.ses at the University of Chicago's graduate school in economics. In Chicago, Brown became enthralled with the mysterious world of stock options. He picked up Thorp's Beat the Market Beat the Market and quickly mastered the book's technique for pricing stock warrants and convertible bonds. In short order, he was doing so well trading options that he considered dropping out of school and pursuing a full-time trading career. Instead, he decided to see through his term at Chicago, while trading on the side. and quickly mastered the book's technique for pricing stock warrants and convertible bonds. In short order, he was doing so well trading options that he considered dropping out of school and pursuing a full-time trading career. Instead, he decided to see through his term at Chicago, while trading on the side.

Brown had no intention of becoming an academic, however. His experience trading options had given him a taste for the real thing. After years playing poker and blackjack in backroom card parlors around the country, he heard the siren song of the world's biggest casino: Wall Street. After graduating in 1982, he moved to New York. His first job was helping to manage the pension plans of large corporations for Prudential Insurance Company of America. A few years later, he took a job as head of mortgage research at Lepercq, de Neuflize & Co., a boutique investment advisor in New York.

With each move, Brown delved more deeply into quantdom. At the time, quants were seen as second-cla.s.s citizens at most trading firms, computer nerds who didn't have the b.a.l.l.s to take the kinds of risks that yielded the real money. Brown got sick of seeing the same rich kids he'd suckered at Harvard lord it over the quants in trading-floor games such as Liar's Poker. That's when he decided to bust up Liar's Poker with quant wizardry.

At Lepercq he picked up a new quant skill: the dark art of securitization. Securitization was a hot new business on Wall Street in the mid-1980s. Bankers would purchase loans such as mortgages from thrifts or commercial banks and bundle them up into securities (hence the name). They would slice those securities into tranches and sell off the pieces to investors such as pension funds and insurance companies. Brown quickly learned how to carve up mortgages into slices with all the dexterity of a professional chef.

Prior to the securitization boom, home loans were largely the province of community-based lenders who lived and died by the time-honored business of borrowing cheap and lending at higher rates. A loan was made by the bank and stayed with the bank until it was paid off. Think Jimmy Stewart and the Bailey Building & Loan a.s.sociation of the Frank Capra cla.s.sic It's a Wonderful Life It's a Wonderful Life. It was such a stolid business that local bankers lived by what some called the "rule of threes": borrow money at 3 percent, lend it to home buyers at three points higher, and be on the golf course by three.

But as baby boomers started buying new homes in the 1970s, Wall Street noticed an opportunity. Many savings and loans didn't have enough capital to satisfy the demand for new loans, especially in Sunbelt states such as California and Florida. Rust Belt thrifts, meanwhile, had too much capital and too little demand. A Salomon bond trader named Bob Dall saw an opening to bring the two together through the financial alchemy of securitization. Salomon would be the middleman, s.h.i.+fting stagnant a.s.sets from the Rust Belt to the Sunbelt, plucking out a portion of the money for itself along the way. To trade the newly created bonds, he turned to Lewis Ranieri, a thirty-year-old trader from Brooklyn working on the bank's utility bond desk.

Over the next few years, Ranieri and colleagues fanned out across the United States, wooing bankers and lawmakers to their bold vision. Mortgage loans made by local banks and thrifts were purchased by Salomon, repackaged into tradable bonds, and sold around the globe. And everybody was happy. Homeowners had access to loans, often at a cheaper interest rate, since there was more demand for the loans from Wall Street. The S&Ls no longer had to worry about borrowers defaulting, because the default risk had been s.h.i.+fted to investors. The banks gobbled up a tidy chunk of middleman fees. And investors could get custom-made, relatively low-risk a.s.sets. It was quant heaven.

The Salomon wizards didn't stop there. Like car salesmen always looking to lure buyers and increase share with s.h.i.+ny new models, they began to concoct something called collateralized mortgage obligations, or CMOs, bondlike certificates built from different tranches of a pool of mortgage-backed securities. (A mortgage-backed security is a bunch of loans sliced into tranches; a CMO is a bunch of those tranches sliced into even more tranches.) The first CMO deal had four tranches worth about $20 million. The tranches were divided into various levels of quality and maturity that spit out different interest payments-as always, greater risk resulting in greater reward. An ancillary benefit, for the banks at least, was that investors who bought these CMOs took on the risk if the underlying loans defaulted or if borrowers refinanced their loans in the event interest rates s.h.i.+fted lower.

That's where quants such as Brown entered the scene. As Ranieri once said, "Mortgages are math." With the rising levels of complexity, all those tricky tranches (there would soon be CMOs with a hundred tranches, each one carrying a somewhat different mix of risk and reward), the devil was in figuring out how to price the a.s.sets. The quants pulled out their calculators, cracked open their calculus books, and came up with solutions.

With the math whizzes at the helm, it was a relatively safe business, give or take the odd, predictable blowup every few years. Brown ran Lepercq's securitization business with a steady hand. The bank had tight relations.h.i.+ps with local bankers throughout the country. If Brown had questions about a loan he was packaging, he could call up the banker directly and ask about it. "Sure, I just drove by that house the other day, he's putting in a new garage," the banker might say.

But in the late 1980s, Lepercq's business was overwhelmed when Salomon ma.s.sively ramped up its mortgage securitization business. Salomon poured billions into the business, bidding for every loan it could get its hands on. A single deal by Salomon could match the entire year's product at Lepercq. Small dealers such as Lepercq couldn't compete. Salomon didn't just offer better deals for loans to the bankers Brown was dealing with-Salomon bought the bank. And it didn't stop at home mortgages. Securitization was the flavor of the financial future, and the future belonged to whoever controlled the supply.

Salomon was soon securitizing every kind of loan known to man: credit cards, car purchases, student loans, junk bonds. As profits kept increasing, so did its appet.i.te and capacity for risk. In the 1990s, it started securitizing riskier loans to borderline borrowers who as a cla.s.s came to be known as subprime.

Wall Street's securitization wizards also made use of a relatively new accounting trick called "off-balance-sheet accounting." Banks created trusts or sh.e.l.l companies in offsh.o.r.e tax havens such as the Cayman Islands or Dublin. The trusts would buy loans, stick them in a "warehouse," and package them up like Christmas presents with bows on top (all through the cybermagic of electronic transfers). The bank didn't need to set aside much capital on its balance sheet, since it didn't own the loans. It was simply acting as middleman, shuffling a.s.sets between buyers and sellers in the frictionless ether of securitization.

The system was extremely profitable due to all the sweet, sweet fees. Guys such as Aaron Brown either jumped on board or moved on to other things.

Brown moved on. Several top firms offered him jobs after he left Lepercq, but he turned them down, eager to get away from the Wall Street rat race. He started teaching finance and accounting courses at Fordham University and Yes.h.i.+va University in Manhattan while keeping his hand in the game by taking the odd consulting job. Consulting at J. P. Morgan, he helped design a revolutionary risk management system for a group that eventually became an independent company called RiskMetrics, a top risk management shop.

Securitization, meanwhile, took off like a freight train in the early 1990s after the savings and loan crisis, when the federal Resolution Trust Corporation took over defaulted savings and loans that once held more than $400 billion of a.s.sets. The RTC bundled up the high-yielding, risky loans and sold them in just a few years, whetting the investors' appet.i.tes for more.

In 1998, Brown took a consulting job with Rabobank, a staid Dutch firm that had started dabbling in credit derivatives. He was introduced to the exciting world of credit default swaps and created a number of trading systems for the new derivatives. It was still the Wild West of the swap market, and there was lots of low-hanging fruit to be had with creative trading.

Credit default swaps may sound fiendishly complex, but they're actually relatively simple instruments. Imagine a family-call it the Bonds family-moves into a beautiful new home worth $1 million recently built in your neighborhood. The local bank has given the Bondses a mortgage. Trouble is, the bank has too many loans on its books and would like to get some of them off its balance sheet. The bank approaches you and your neighbors and asks whether you would be interested in providing insurance against the chance that the Bonds family may one day default.

Of course, the bank will pay you a fee, but nothing extravagant. Mr. and Mrs. Bonds are hardworking. The economy is in solid shape. You think it's a good bet. The bank starts paying you $10,000 a year. If Mr. and Mrs. Bonds default, you owe $1 million. But as long as Mr. and Mrs. Bonds keep paying their mortgage, everything is fine. It's almost like free money. In essence, you've bought a credit default swap on Mr. and Mrs. Bonds's house.

One day you notice that Mr. Bonds didn't drive to work in the morning. Later you find out that he's lost his job. Suddenly you're worried that you may be on the hook for $1 million. But wait: another neighbor, who thinks he knows the family better than you, is confident that Mr. Bonds will get his job back soon. He's willing to take over the responsibility for that debt-for a price, of course. He wants $20,000 a year to insure the Bondses' mortgage. That's bad news for you, since you have to pay an extra $10,000 a year-but you think it's worth it because you really don't want to pay for that $1 million mortgage.

Welcome to the world of credit default swaps trading.

Many CDS traders, such as Weinstein, weren't really in the game to protect themselves against a loss on a bond or mortgage. Often these investors never actually held the debt in the first place. Instead, they were gambling on the perception perception of whether a company would default or not. of whether a company would default or not.

If all of this weren't strange enough, things became truly surreal when the world of credit default swaps met the world of securitization. Brown had watched, with some horror, as banks started to bundle securitized loans into a product they called a collateralized debt obligation, or CDO. CDOs were similar to the CMOs (collateralized mortgage obligations) Brown had encountered in the 1980s. But they were more diverse and could be used to package any kind of debt, from mortgages to student loans to credit card debt. Some CDOs were made up of other pieces of CDOs, a Frankenstein-like beast known as CDO-squared. (Eventually there were even CDOs of CDOs of CDOs.) Just when things seemingly couldn't get stranger, CDOs underwent a completely new twist when a team of J. P. Morgan quants created one of the most bizarre and ultimately destructive financial products ever designed: the "synthetic" CDO.

In the mid-1990s, a New York group of J. P. Morgan financial engineers began thinking about how to solve a problem that plagued the bank: a huge inventory of loans on the bank's balance sheet that was earning paltry returns. Because the bank was limited in how many loans it could make due to capital reserve requirements, those loans were holding it back. What if there was a way to make the risk of the loans disappear?

Enter the credit default swap. The bank came up with the novel idea of creating a synthetic CDO using swaps. The swaps were tied to the loans that had been sitting on J. P. Morgan's balance sheet, repackaged into a CDO. Investors, instead of buying an actual bundle of bonds-getting the yield on the bonds, but also a.s.suming the risk of default-were instead agreeing to insure insure a bundle of bonds, getting paid by a premium to do so. a bundle of bonds, getting paid by a premium to do so.

Imagine, in other words, thousands of swaps tied to bundles of mortgages (or other kinds of loans such as corporate and credit card debt) such as those owned by Mr. and Mrs. Bonds.

By selling slices of synthetic CDOs to investors, J. P. Morgan offloaded the risk of the debt it held on its balance sheet. Since the bank was essentially insuring the loans, it didn't need to worry anymore about the risk the loan holder would default. With that-presto change-o-the bank could use more capital to make more loans ... and book more fees.

It was brilliant, on paper. In December 1997, J. P. Morgan's New York derivatives desk unveiled its masterpiece of financial engineering. It was called Bistro, short for Broad Index Secured Trust Offering. Bistro was a high-powered vacuum cleaner for a bank's credit exposure, an industrialized risk management tool. The first Bistro deal allowed J. P. Morgan to unload nearly $1 billion in credit risk from its balance sheet on a portfolio of $10 billion in loans. The bank retained a certain part of the synthetic CDO in the form of a high-grade "super-senior" tranche, which had been deemed so safe that there was virtually no chance that it would ever see losses. This fizzing concoction would play a critical role in the credit meltdown of 2007 and 2008.

As time went on, more and more credit default swaps, or tranches of them, spread through the financial system. Traders such as Boaz Weinstein scooped them up like racetrack gamblers betting on which horse would finish last. In certain ways, the whole increasingly complex derivatives fantasia harkened back to the block-trading desk at Morgan Stanley in the early 1980s when Gerry Bamberger came up with the idea of statistical arbitrage: an idea that started off as a risk management tool had turned into a casino. But Bamberger's creation was kid stuff compared to the industrial-strength mathematical nightmare cooked up in the quant labs of J. P. Morgan. Complexity built upon complexity. Soon it went viral.

In 1998, the Russian government defaulted on its bonds and Long-Term Capital Management collapsed. The resulting chaos helped to turbocharge the credit derivatives industry (helping set the stage for the rise of Boaz Weinstein). Everyone wanted a piece of these arcane swaps, since they provided a form of protection against the risk of default. J. P. Morgan pumped new products into the system as it Bistro'd up its balance sheet. Other banks quickly followed suit. A robust secondary market for credit default swaps sprang up in which traders such as Weinstein made bets on whether they were mis-priced.

Brown, meanwhile, went back to full-time work at Citigroup in 2000, working on a firmwide risk management system for the largest bank in the world. He found that Citi had much of its risk under control. But one corner of the bank bothered him: securitization. Since the bank's securitization activities took place "off balance sheet," in offsh.o.r.e accounts, there was a disturbing lack of transparency. It was hard to know exactly what was going on, how much risk was being taken. There seemed little he could do about it, aside from complaining to management from time to time. But who would listen? The business was a profit juggernaut. Naysayers were ignored.

Brown watched as the relatively sedate financial system he'd joined in the 1980s turned into a derivatives-laden, debt-grinding monster. Banks were dabbling in the most exotic derivatives imaginable. Blowups were becoming more frequent, but they seemed dwarfed by the ma.s.sive amounts of money coming in the door. The casino stayed open for business. Indeed, it started branching out, searching for more ways to pull in capital its traders could play around with. For instance, subprime mortgages.

Like most Wall Streeters, however, Aaron Brown was dazzled by the numbers, by the ingenious trading strategies that could arb out inefficiencies and deliver seemingly endless profits. Indeed, virtually the entire quant community, aside from a few random party-p.o.o.pers, embraced the derivatives explosion wholeheartedly. The layered levels of complexity didn't bother them whatsoever. They loved it. Wall Streeters, however, Aaron Brown was dazzled by the numbers, by the ingenious trading strategies that could arb out inefficiencies and deliver seemingly endless profits. Indeed, virtually the entire quant community, aside from a few random party-p.o.o.pers, embraced the derivatives explosion wholeheartedly. The layered levels of complexity didn't bother them whatsoever. They loved it.

Perhaps the most egregious example of over-the-top quant.i.tative creativity involved those synthetic CDOs such as J. P. Morgan's Bistro. Because of the complexity of all of their tangled and tranched swaps and bonds, it was very difficult to price all of the pieces. The biggest problem was the one Weinstein focused on years later: correlation. If loans in one piece of the CDO weaken, what are the odds that loans in other parts will see problems? It's the same problem as asking whether all the apples in a bag will start to rot if a few go bad.

Naturally, a quant was waiting in the wings with an elegant solution to it all-a solution that would help drive global credit markets into a ditch several years later.

That solution came from a Chinese-born quant named David X. Li, a financial engineer at the New York headquarters of the Canadian Imperial Bank of Commerce, or CIBC. Rather than try to model all of the fiendishly difficult factors that make the pricing of all the interrelated pieces so th.o.r.n.y, Li hit upon a quick fix that would immediately provide the data to price the hodgepodge of CDO tranches.

Li often discussed the problem with colleagues from academia who were experts in an actuarial science called survival a.n.a.lysis. One concept they studied was the fact that after the death of a spouse, people tend to die sooner than their demographic peers. In other words, they were measuring correlations between the deaths of spouses.

The link between dying spouses and credit default swaps was quant wizardry at its best-and its worst. Li showed how this model could a.s.sign correlations between tranches of CDOs by measuring the price of credit default swaps linked to the underlying debt. Credit default swaps supply a single variable that incorporates the market's a.s.sessment of how the loan will perform. The price of a CDS, after all, is simply a reflection of the view investors have on whether or not a borrower will default.

Li's model supplied a method to bundle the prices of many different credit default swaps in a CDO and spit out numbers showing the correlations between the tranches. In April 2000, having moved on to J. P. Morgan's credit department, he published his results in the Journal of Fixed Income Journal of Fixed Income in a paper called "On Default Correlation: A Copula Function Approach." The model's name was based in part on the statistical method he used to measure correlations: the Gaussian copula. in a paper called "On Default Correlation: A Copula Function Approach." The model's name was based in part on the statistical method he used to measure correlations: the Gaussian copula.

Copulas are mathematical functions that calculate the connections between two variables-in other words, how they "copulate." When X happens (such as a homeowner defaulting), there's a Y chance that Z happens (a neighboring homeowner defaults). The specific copulas Li used were named after Carl Friedrich Gauss, the nineteenth-century German mathematician known for devising a method, based on the bell curve, to measure the motion of stars.

The correlations between the slices in a CDO were, therefore, based on the bell curve (a copula is essentially a multidimensional bell curve). Thousands of bonds (or the swaps linked to them) weren't expected to make big, sudden jumps; rather, they were generally expected to move from one point to another, up or down, in relatively predictable patterns. Extreme moves in a large number of underlying bonds weren't part of the model. It was the law of large numbers all over again, the same mathematical trick Ed Thorp used to beat blackjack in the 1960s and that Black and Scholes used to price options. Now, however, it was being applied on a scale so vast and complex that it approached the absurd. Undaunted, the quants lapped it up.

As the synthetic CDO market boomed, Wall Street and credit rating agencies adopted Li's model. "The Gaussian copula was the Black-Scholes for credit derivates," said Michel Crouhy, Li's boss at CIBC in the 1990s. So-called correlation traders sprang up at banks such as Goldman Sachs, Morgan Stanley, and Deutsche Bank, using the model to trade CDO tranches, and the underlying correlations between them, like baseball cards. The model seemed to work relatively well and was easy to use.

Crucially, and disastrously, the model was based on how other investors other investors viewed the market through the lens of credit default swaps. If CDS traders thought few homeowners would default on their loans, Li's Gaussian copula priced the tranches accordingly. And since the CDO boom was occurring at the same time that a housing bubble was inflating-indeed, it helped inflate the bubble-most investors believed there was little chance that a large number of loans would default. What resulted was a vicious feedback loop-an echo chamber, one might say-in which enthusiastic investors snapped up tranches of CDOs, creating demand for more CDOs-and that created a demand for more mortgage loans. The CDOs were showing very little risk, according to Li's model. For some reason, nearly everyone, except for a few doubting Thomases in the wilderness, believed in it, even though the historical record of how mortgage loans behaved in a broad economic downturn was vanis.h.i.+ngly slim. viewed the market through the lens of credit default swaps. If CDS traders thought few homeowners would default on their loans, Li's Gaussian copula priced the tranches accordingly. And since the CDO boom was occurring at the same time that a housing bubble was inflating-indeed, it helped inflate the bubble-most investors believed there was little chance that a large number of loans would default. What resulted was a vicious feedback loop-an echo chamber, one might say-in which enthusiastic investors snapped up tranches of CDOs, creating demand for more CDOs-and that created a demand for more mortgage loans. The CDOs were showing very little risk, according to Li's model. For some reason, nearly everyone, except for a few doubting Thomases in the wilderness, believed in it, even though the historical record of how mortgage loans behaved in a broad economic downturn was vanis.h.i.+ngly slim.

Then, in 2004, to meet the insatiable demand, banks started packing CDOs with a type of loan Li hadn't considered when creating his model in the late 1990s: subprime mortgages. The CDO market went into hyperdrive.

Thanks to even more quant alchemy, certain tranches of subprime CDOs could earn AAA ratings from agencies such as Standard & Poor's, a stamp of approval that allowed regulated ent.i.ties such as pension funds to gobble them up. Here's how it worked: Financial engineers would take lower-rated slices of a mortgage-backed security or other securitized bundle of loans such as credit card lines, and package them in a CDO. It would then slice the CDO into different pieces, based on priority-which slices had the right to the cash spit out by the loans first, second, third, and so on. A product that began as home loans to the riskiest kind of borrower went through the looking gla.s.s of quantdom and came out a gold-plated security, suitable for some of the most closely watched and regulated investors. In fact, they were only low-risk relative to other, even more volatile tranches, when viewed through the rose-colored gla.s.ses of boom-time investors.

In 2004, $157 billion in CDOs was issued, much of which contained subprime mortgages. The amount spiked to $273 billion in 2005 and a whopping $550 billion in 2006, its peak year.

The Gaussian copula was, in hindsight, a disaster. The simplicity of the model hypnotized traders into thinking that it was a reflection of reality. In fact, the model was a jury-rigged formula based on the irrationally exuberant, self-reinforcing, and ultimately false wisdom of the crowd that a.s.signed make-believe prices to an incredibly complex product. For a while it worked, and everyone was using it. But when the slightest bit of volatility hit in early 2007, the whole edifice fell apart. The prices didn't make sense anymore. Since nearly every CDO manager and trader used the same formula to price the fizzing bundles-yet another instance of crowding that results from popular quant methodologies-they all imploded at once.

Is it any wonder why? The complexity had become malevolent. The quants and correlation traders were modeling cash flows on tranches of credit default swaps tied to CDOs that were bundles of mortgage-backed securities, which in turn were tranched packages of opaque loans from homeowners around the country. The model created an illusion of order where none existed.

A key player in the CDO boom was a Citadel baby, a $5 billion hedge fund called Magnetar Capital run by one of Ken Griffin's star traders, Alec Litowitz. In 2006, Total Securitization Total Securitization, an industry newsletter, named Magnetar investor of the year. "Magnetar bought bespoke deals in ma.s.sive size in 2006, investing in a series of CDOs-each over $1 billion," the newsletter said in March 2007.

Magnetar's presence in the CDO world can be found in Litowitz's seeming fascination with astronomy. A large number of toxic CDOs created at the height of the subprime frenzy had astronomical names, such as Orion, Aquarius, Scorpius, Carina, and Sagittarius. Magnetar was "their lynchpin investor," according to an investigation by the Wall Street Journal Wall Street Journal. But Magnetar, which gained 25 percent in 2007, was also taking the other side of slices of those CDOs, buying positions that would pay off when higher-rated slices turned sour.

Magnetar's trade was ingenious, and possibly diabolical. It would hold the riskiest slices of CDOs, known as the "equity"-those most vulnerable to defaults. But it also was buying protection on less-risky slices higher up the stack of the CDO's structure, essentially betting on a wave of defaults. The roughly 20 percent yield on the equity slices provided the cash to purchase the less-risky slices. If the equity imploded, as it did, the losses would mean little if the higher-quality slices also saw significant losses, which they did.

In hindsight, Magnetar turned out to be a facilitator of the CDO boom, because it gobbled up those equity slices when few other investors wanted to buy them. Without a willing buyer of the junk slices, banks would have had a much harder time constructing the increasingly dicey CDOs. .h.i.tting the market in 2006 and 2007. In all, Magnetar was a key investor in roughly $30 billion of constellation CDOs issued from mid-2006 to mid-2007.

There's clear evidence that Wall Street's gluttonous demand for loans and all the fat fees they spit out was the key factor that allowed, and encouraged, brokers to concoct increasingly risky mortgages with toxic bells and whistles such as adjustable interest rates that shot higher a few years-or in some cases a few months-after the loan was made. Out of twenty-five of the top subprime mortgage lenders, twenty-one were either owned or financed by major Wall Street or European banks, according to a report by the Center for Public Integrity. Without the demand from the investment banks, the bad loans would never have been made.

As the CDO boom took off, so did home prices across the United States. From January 2000 through July 2006, the peak of the housing bubble, the average price of a home in the United States rose 106 percent, according to the S&P/Case-s.h.i.+ller National Home Price Index. To models such as the Gaussian copula, the message was clear: the housing market was getting safer and safer. In fact, it was getting far more dangerous. In late 2006, the home price index started to move in the opposite direction, falling more than 30 percent three years later.

Some quants, including Brown himself, criticized the models that banks and credit rating agencies were using to price CDOs. He knew the correlations spat out by the Gaussian copula were a fantasy. But as long as the money was rolling in, no one wanted to hear it-not the correlation traders making fat bonuses, and definitely not the Wall Street CEOs making even fatter bonuses.

Like crack cocaine, it was addictive, and ultimately ruinous. While the boom lasted, securitization helped Wall Street become an increasingly powerful force in the U.S. economy. The financial sector's share of total U.S. corporate profits. .h.i.t 35 percent in 2007, up from 10 percent in the early 1980s, when quants such as Brown started to arrive on the scene. Financial inst.i.tutions made up one-fourth of the market cap of the S&P 500, far more than any other industry.

Helping to drive the surge in financial profits was that clever tactic favored by funds such as AQR, Global Alpha, Citadel, and Saba: the carry trade. By late 2006, more money than ever had been plowed into the trade, in which investors, usually banks and hedge funds, borrowed low-yielding currencies such as j.a.panese yen to buy higher-yielding currencies such as the New Zealand dollar or British pound. It was a frictionless digital push-b.u.t.ton cash machine based on math and computers-a veritable quant fantasyland of riches.

The carry trade was fueling a worldwide liquidity boom, sparking a frenzy in everything from commodities to real estate-and subprime mortgages. "They can borrow at near zero interest rates in j.a.pan ... to relend anywhere in the world that offers higher yields, whether Argentine notes or U.S. mortgage securities," marveled the United Kingdom newspaper the Telegraph Telegraph. "It has prolonged a.s.set bubbles everywhere."