In Which the Whys Didn’t Matter

The latest book from Gregory Zuckerman is an ideal companion on the reading table next to whatever it is you haven’t read by Michael Lewis, the author who has replaced Tom WolfeThe Electric Kool-Aid Acid Test (1968), “The Me Decade and the Third Great Awakening” (1976), Bonfire of the Vanities (1987), A Man in Full (1998) – as the premier storyteller of his age.

Lewis, from Liar’s Poker: Rising through the Wreckage on Wall Street (1989 about Salomon Brothers’ John Gutfreund and financial deregulation) and The New New Thing: A Silicon Valley Story (1999, about software entrepreneur Jim Clark and the browser wars that followed the invention of the World Wide Web); to Moneyball: The Art of Winning an Unfair Game (2003, about new-fangled baseball analytics and Oakland Athletics general manager Billy Bean) to The Blind Side: Evolution of a Game (2006, about new-fangled football analytics and left tackle Michael Oher),  has illuminated major changes in familiar institutions,  in always entertaining but sometimes misleading ways.

After the 2007-08 financial crisis, Lewis published The Big Short: Inside the Doomsday Machine (2010, about the use of credit default swaps to bet against the subprime mortgage market), followed by Flash Boys: A Wall Street Revolt (2014, about high-frequency trading).

Zuckerman, who has the advantage of being a special writer for The Wall Street Journal, is the journalist who gets those changes more nearly right, on the stories on which he and Lewis compete.

The Big Short is about Michael Burry, the physician-turned-hedge-fund-operator who recognized the possibilities inherent in the subprime bubble but who failed to get the timing right. Zuckerman’s The Greatest Trade Ever: The Behind-the-Scenes Story of How John Paulson Defied Wall Street and Made Financial History (2009) tells the story of the money manager who made $15 billion for his investors – and $4  billion for himself – by  getting the bet down right.

Zuckerman’s new book is The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution (2019).  In between he wrote The Frackers: The Outrageous Inside Story of the New Billionaire Wildcatters (2013).  When Simons stepped down as head of Renaissance Technologies Corp., in 2009, he was worth more than $11 billion, accumulated in the course of nearly constant trading – a more daunting task, perhaps, than scoring a single brilliant success, as Paulson’s post-2008 experience suggests.

The new book’s title is not quite right.  There were plenty of quants before Simons quit the math department at the State University of New York at Stony Brook , many of them making good money. (See The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (2010), by Scott Patterson, More Money Than God: Hedge Funds and the Making of a New Elite (2011) by Sebastian Mallaby). What set Simons apart was his drive to make the most money from his considerable skills as a professor of mathematics, in collaboration with others possessing an academic degree or skill at the same level.

Nor is the account quite as inside as Zuckerman’s other books.  Simons declined to talk to him until fairly late in the game, and then only about certain topics, not including his still-secret recipes. Zuckerman had to work harder for this yarn than he did for the Paulson story, which featured a full-page portrait of its subject opposite the title page.

Simons, a well-adjusted prodigy, grew up in Newton, Mass. and attended Brookline’s Lawrence School.  He discovered as an undergraduate at The Massachusetts Institute of Technology that he wasn’t quite at the top level of contemporaries in math, including fellow student Barry Mazur.  He was, however, close enough to sail through his math PhD at the University of California at Berkeley in three years, before returning, in 1962, to Cambridge to teach.

Bored, Simons quit after a year to become a code-breaker at the Institute for Defense Analysis (IDA), a Pentagon contractor in Princeton, N.J.  In 1968, in collaboration with a Princeton University professor, he published a path-breaking paper in differential geometry that assured his reputation. But Simons had acquired a taste in California for commodity trading, and in his spare-time as a code breaker he and three colleagues published a stock-trading scheme.  Zuckerman writes,

Here’s what was really unique. The paper didn’t try to identify or predict [various market] states using economic theory or other conventional methods, nor did the researchers seek to address why the market entered certain states.  Simons and his colleagues used mathematics to determine the set of states best fitting the observed pricing data; their model then made its bet accordingly. The whys didn’t matter, Simons and his colleagues seem to suggest, just the strategies to take advantage of the inferred states.

One thing led to another. In 1968, at the age of 30, Simons left IDA for Stony Brook, on the north shore of Long Island, where the university administration had set out to establish a mathematics department strong enough to complement its world-class biology department. In 1976 he was recognized with the Oswald Veblen Prize, the profession’s highest honor in geometry. Two years after that, he quit the university and rented a storefront office in a strip mall across from the Stony Brook railroad station as proprietor of Monemetrics, a currency-trading firm, and Limroy, a tiny hedge-fund.  A year later, two other distinguished mathematicians signed on as his partners.

It wasn’t a smooth beginning. Partners came and went. Mergers and acquisitions flourished, and with them the return to inside information – the opposite of the advantage Simons sought.  But computer power doubled every two years, according to Moore’s Law, while prices fell by half.  Simons changed his firm’s name to Renaissance Technologies.

By 1991 the talk of Wall Street was a former Columbia University computer science professor named David Shaw. He had learned the techniques of statistical arbitrage at Morgan Stanley before the old-line investment bank slashed the funding of one of its most profitable units after it had a bad year.  Now, backed by veteran bond trader Donald Sussman, Shaw’s startup was the cutting edge of computer-based trading strategies.

Simons understood that, in order to compete with Shaw, he would need to develop new methods. Financial backers whom he sought, including legendary Commodities Corp., turned him down Among those he hired was mathematician Henry Laufer, a former Stony Brook colleague with a knack for programming.   And among those Laufer hired was a British code-breaker named Greg Patterson now working at the IDA.

Patterson possessed a special advantage. As a Brit, trained in the out-of-style methods that enabled British cryptographers to decipher the Germans’ wartime Enigma code, he was aware of new computer-based applications of Bayesian statistics.  These were techniques based on the fundamental insight of Rev. Thomas Bayes, an eighteenth-century amateur mathematician that, by periodically updating one’s initial presuppositions with newly arrived objective information, one could continually improve one’s understanding of many matters. For an especially clear account of the history of Bayes’ Theorem, see The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy (2011), by veteran science writer Sharon Bertsch McGrayne

In 1992, the cynosure of the Bayesian community was the little group of computational linguists at IBM Corp. that had run rings around a competing team of linguistics theorists working on machine translation – by the simple expedient of feeding into its powerful  computers decades of French-English translations of Canadian parliamentary debates.  The computers were armed with machine-learning algorithms that had been instructed to search for patterns.  Ever-more dependable translation patterns emerged.

When Patterson learned that IBM was reluctant to permit its team leaders to commercialize their discoveries, he hired Robert Mercer and Peter Brown who had been leaders of the team. Laufer had built a platform that permitted trading across asset classes.  It turned out that the methods Mercer and Brown brought with them had wide applicability to the enormous streams of financial data that was becoming ever more plentiful. It was at that point that Renaissance Technologies began to overtake its competitors.

Medallion, the firm’s main fund, earned 71 percent on its capital in 1994, 38 percent in 1995, 31 percent in 1996, and a paltry 21 percent in 1997, a bad year. In 1998, though, D.E. Shaw suffered stinging losses, and Long Term Capital management, Simons’ other main competitor, went bust, after Russia defaulted on its government bonds.  By 2000, Medallion returned 99 percent on the $4 billion invested with it, even after Simons collected 20 percent of the gains and five percent of the total invested.

Simons and his colleagues had indeed “solved the market,” at least until their competitors got wise to their methods, but the tumult didn’t go away. Mercer and Brown gradually took over day-to-day management of the firm.  A couple of disagreeable Ukrainians traders signed on.  The Bayesian Patterson departed for the Broad Institute, in Cambridge, Mass., to work on genomic problems.  And in 2016, the libertarian Mercer, by now a billionaire himself, turned out to be, with his daughter Rebekah, a major strategist and funder of Donald Trump’s presidential campaign. Simons forced his resignation from the firm.  It all makes for fascinating reading.

At one point, Zuckerman jokes that his next book will be about fortunes made in “the golden age of porn.” He  is kidding, and a good thing too.   The still-bigger fortune out there is BlackRock, the $7 trillion asset-management firm founded by Larry Fink and partners in 1987, the year of a great “market break,” after which a great deal of modern financial technology took hold. With such a book, covering the rise of private equity firms as well, a basic map of the major features of twenty-first century finance would be complete.

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