Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (6 page)

Newcomers were required to be on call every thirteen weeks in the futures group. This meant being ready to respond to computer problems whenever any of the world’s markets were open, from Sunday evening our time, when the Asian markets came to life, to New York’s closing bell at 4 p.m. on Friday. Sleep deprivation was an issue. But worse was the powerlessness to respond to issues in a shop that didn’t share information. Say an algorithm appeared to be misbehaving. I’d have to locate it and then find the person responsible for it, at any time of the day or night, and tell him (and it was always a him) to fix it. It wasn’t always a friendly encounter.

Then there were panics. Over holidays, when few people were working, weird things tended to happen. We had all sorts of things in our huge portfolio, including currency forwards, which were promises to buy large amounts of a foreign currency in a couple of days. Instead of actually buying the foreign currency, though, a trader would “roll over” the position each day so the promise
would be put off for one more day. This way, our bet on the direction of the market would be sustained but we’d never have to come up with loads of cash. One time over Christmas I noticed a large position in Japanese yen that was coming due. Someone had to roll that contract over. This was a job typically handled by a colleague in Europe, who presumably was home with his family. I saw that if it didn’t happen soon someone theoretically would have to show up in Tokyo with $50 million in yen. Ironing out that problem added a few frantic hours to the holiday.

All of those issues might fit into the category of occupational hazard. But the real problem came from a nasty feeling I started to have in my stomach. I had grown accustomed to playing in these oceans of currency, bonds, and equities, the trillions of dollars flowing through international markets. But unlike the numbers in my academic models, the figures in my models at the hedge fund stood for something. They were people’s retirement funds and mortgages. In retrospect, this seems blindingly obvious. And of course, I knew it all along, but I hadn’t truly appreciated the nature of the nickels, dimes, and quarters that we pried loose with our mathematical tools. It wasn’t found money, like nuggets from a mine or coins from a sunken Spanish galleon. This wealth was coming out of people’s pockets. For hedge funds, the smuggest of the players on Wall Street, this was “dumb money.”

It was when the markets collapsed in 2008 that the ugly truth struck home in a big way. Even worse than filching dumb money from people’s accounts, the finance industry was in the business of creating WMDs, and I was playing a small part.

The troubles had actually started a year earlier. In July of 2007, “interbank” interest rates spiked. After the recession that followed the terrorist attacks in 2001, low interest rates had fueled a housing boom. Anyone, it seemed, could get a mortgage, builders were turning exurbs, desert, and prairie into vast new housing
developments, and banks gambled billions on all kinds of financial instruments tied to the building bonanza.

But these rising interest rates signaled trouble. Banks were losing trust in each other to pay back overnight loans. They were slowly coming to grips with the dangerous junk they held in their own portfolios and judged, wisely, that others were sitting on just as much risk, if not more. Looking back, you could say the interest rate spikes were actually a sign of sanity, although they obviously came too late.

At Shaw, these jitters dampened the mood a bit. Lots of companies were going to struggle, it was clear. The industry was going to take a hit, perhaps a very big one. But still, it might not be our problem. We didn’t plunge headlong into risky markets. Hedge funds, after all, hedged. That was our nature. Early on, we called the market turbulence “the kerfuffle.” For Shaw, it might cause some discomfort, maybe even an embarrassing episode or two, like when a rich man’s credit card is denied at a fancy restaurant. But there was a good chance we’d be okay.

Hedge funds, after all, didn’t make these markets. They just played in them. That meant that when the market crashed, as it would, rich opportunities would emerge from the wreckage. The game for hedge funds was not so much to ride markets up as to predict the movements within them. Down could be every bit as lucrative.

To understand how hedge funds operate at the margins, picture a World Series game at Chicago’s Wrigley Field. With a dramatic home run in the bottom of the ninth inning, the Cubs win their first championship since 1908, back when Teddy Roosevelt was president. The stadium explodes in celebration. But a single row of fans stays seated, quietly analyzing a slew of results. These gamblers don’t hold the traditional win-or-lose bets. Instead they may have bet that Yankees relievers would give up more walks
than strikeouts, that the game would feature at least one bunt but no more than two, or that the Cubs’ starter would last at least six innings. They even hold bets that other gamblers will win or lose their own bets. These people wager on many movements associated with the game, but not as much on the game itself. In this, they behave like hedge funds.

That made us feel safe, or at least safer. I remember a gala event to celebrate the architects of the system that would soon crash. The firm welcomed Alan Greenspan, the former Fed chairman, and Robert Rubin, the former Treasury secretary and Goldman Sachs executive. Rubin had pushed for a 1999 revision of the Depression-era Glass-Steagall Act. This removed the glass wall between banking and investment operations, which facilitated the orgy of speculation over the following decade. Banks were free to originate loans (many of them fraudulent) and sell them to their customers in the form of securities. That wasn’t so unusual and could be considered a service they did for their customers. However, now that Glass-Steagall was gone, the banks could, and sometimes did, bet against the very same securities that they’d sold to customers. This created mountains of risk—and endless investment potential for hedge funds. We placed our bets, after all, on market movements, up or down, and those markets were frenetic.

At the D. E. Shaw event, Greenspan warned us about problems in mortgage-backed securities. That memory nagged me when I realized a couple of years later that Rubin, who at the time worked at Citigroup, had been instrumental in collecting a massive portfolio of these exact toxic contracts—a major reason Citigroup later had to be bailed out at taxpayer expense.

Sitting with these two was Rubin’s protégé and our part-time partner, Larry Summers. He had followed Rubin in Treasury and had gone on to serve as president of Harvard University. Summers
had troubles with faculty, though. And professors had risen up against him in part because he suggested that the low numbers of women in math and the hard sciences might be due to genetic inferiority—what he called the unequal distribution of “intrinsic aptitude.”

After Summers left the Harvard presidency, he landed at Shaw. And I remember that when it came time for our founder, David Shaw, to address the prestigious trio, he joked that Summers’s move from Harvard to Shaw had been a “promotion.” The markets might be rumbling, but Shaw was still on top of the world.

Yet as the crisis deepened the partners at Shaw lost a bit of their swagger. Troubled markets, after all, were entwined. For example, rumors were already circulating about the vulnerability of Lehman Brothers, which owned 20 percent of D. E. Shaw and handled many of our transactions. As the markets continued to rattle and shake, the internal mood turned fretful. We could crunch numbers with the best of the best. But what if the frightening tomorrow on the horizon didn’t resemble any of the yesterdays? What if it was something entirely new and different?

That
was a concern, because mathematical models, by their nature, are based on the past, and on the assumption that patterns will repeat. Before long, the equities group liquidated its holdings, at substantial cost. And the hiring spree for new quants, which had brought me to the firm, ended. Although people tried to laugh off this new climate, there was a growing fear. All eyes were on securitized products, especially the mortgage-backed securities Greenspan had warned us about.

For decades, mortgage securities had been the opposite of scary. They were boring financial instruments that individuals and investment funds alike used to diversify their portfolios. The idea behind them was that quantity could offset risk. Each single mortgage held potential for default: the home owner could
declare bankruptcy, meaning the bank would never be able to recover all of the money it had loaned. At the other extreme, the borrower could pay back the mortgage ahead of schedule, bringing the flow of interest payments to a halt.

And so in the 1980s, investment bankers started to buy thousands of mortgages and package them into securities—a kind of bond, which is to say an instrument that pays regular dividends, often at quarterly intervals. A few of the home owners would default, of course. But most people would stay afloat and keep paying their mortgages, generating a smooth and predictable flow of revenue. In time, these bonds grew into an entire industry, a pillar of the capital markets. Experts grouped the mortgages into different classes, or tranches. Some were considered rock solid. Others carried more risk—and higher interest rates. Investors had reason to feel confident because the credit-rating agencies, Standard & Poor’s, Moody’s, and Fitch, had studied the securities and scored them for risk. They considered them sensible investments. But consider the opacity. Investors remained blind to the quality of the mortgages in the securities. Their only glimpse of what lurked inside came from analyst ratings. And these analysts collected fees from the very companies whose products they were rating. Mortgage-backed securities, needless to say, were an ideal platform for fraud.

If you want a metaphor, one commonly used in this field comes from sausages. Think of the mortgages as little pieces of meat of varying quality, and think of the mortgage-backed securities as bundles of the sausage that result from throwing everything together and adding a bunch of strong spices. Of course, sausages can vary in quality, and it’s hard to tell from the outside what went into them, but since they have a stamp from the USDA saying they’re safe to eat, our worries are put aside.

As the world later learned, mortgage companies were making
rich profits during the boom by loaning money to people for homes they couldn’t afford. The strategy was simply to write unsustainable mortgages, snarf up the fees, and then unload the resulting securities—the sausages—into the booming mortgage security market. In one notorious case, a strawberry picker named
Alberto Ramirez, who made $14,000 a year, managed to finance a $720,000 house in Rancho Grande, California. His broker apparently told him that he could refinance in a few months and later flip the house and make a tidy profit. Months later, he defaulted on the loan.

In the run-up to the housing collapse, mortgage banks were not only offering unsustainable deals but actively prospecting for victims in poor and minority neighborhoods. In a federal lawsuit,
Baltimore officials charged Wells Fargo with targeting black neighborhoods for so-called ghetto loans. The bank’s “emerging markets” unit, according to
a former bank loan officer, Beth Jacobson, focused on black churches. The idea was that trusted pastors would steer their congregants toward loans. These turned out to be subprime loans carrying the highest interest rates. The bank sold these even to borrowers with rock-solid credit, who should have qualified for loans with far better terms. By the time Baltimore filed the suit, in 2009, more than half of the properties subject to foreclosure on Well Fargo loans were empty, and 71
percent of them were in largely African American neighborhoods. (In 2012,
Wells Fargo settled the suit, agreeing to pay $175 million to thirty thousand victims around the country.)

To be clear, the subprime mortgages that piled up during the housing boom, whether held by strawberry pickers in California or struggling black congregants in Baltimore, were not WMDs. They were financial instruments, not models, and they had little to do with math. (In fact, the brokers went to great lengths to ignore inconvenient numbers.)

But when banks started loading mortgages like Alberto Ramirez’s into classes of securities and selling them, they were relying on flawed mathematical models to do it. The risk model attached to mortgage-backed securities was a WMD. The banks were aware that some of the mortgages were sure to default. But banks held on to two false assumptions, which sustained their confidence in the system.

The first false assumption was that crack mathematicians in all of these companies were crunching the numbers and ever so carefully balancing the risk. The bonds were marketed as products whose risk was assessed by specialists using cutting-edge algorithms. Unfortunately, this just wasn’t the case. As with so many WMDs, the math was directed against the consumer as a smoke screen. Its purpose was only to optimize short-term profits for the sellers. And those sellers trusted that they’d manage to unload the securities before they exploded. Smart people would win. And dumber people, the providers of dumb money, would wind up holding billions (or trillions) of unpayable IOUs. Even rigorous mathematicians—and there were a few—were working with numbers provided by people carrying out wide-scale fraud. Very few people had the expertise and the information required to know what was actually going on statistically, and most of the people who did lacked the integrity to speak up. The risk ratings on the securities were designed to be opaque and mathematically intimidating, in part so that buyers wouldn’t perceive the true level of risk associated with the contracts they owned.

The second false assumption was that not many people would default at the same time. This was based on the theory, soon to be disproven, that defaults were largely random and unrelated events. This led to a belief that solid mortgages would offset the losers in each tranche. The risk models were assuming that the future would be no different from the past.

In order to sell these mortgage-backed bonds, the banks needed AAA ratings. For this, they looked to the three credit-rating agencies. As the market expanded, rating the growing billion-dollar market in mortgage bonds turned into a big business for the agencies, bringing in lucrative fees. They grew addicted to those fees. And they understood all too clearly that if they provided anything less than AAA ratings, the banks would take the work to their competitors. So the agencies played ball. They paid more attention to customer satisfaction than to the accuracy of their models. These risk models also created their own pernicious feedback loop. The AAA ratings on defective products turned into dollars. The dollars in turn created confidence in the products and in the cheating-and-lying process that manufactured them. The resulting cycle of mutual back-scratching and pocket-filling was how the whole sordid business operated until it blew up.