Nerds on Wall Street Eli Lehrer; Karl Zinsmeister 3,240 words 1 July 2002 American Enterprise 4649 Volume 13, Issue 5; ISSN: 1047-3572 English Copyright (c) 2002 ProQuest Information and Learning. All rights reserved. Copyright American Enterprise Institute for Public Policy Research Jul/Aug 2002 Success in America's thriving, often cutthroat, finance industry has always required finding individuals and building organizations with a wide range of skills. Persuasive sales people, statistical gurus, and instinctual risk takers have all had a place in the business. But much more than a generation ago, Wall Street is now peopled by apparently unrelated, even seemingly conflicting, groups. Aggressive, brash, flashy men (they are almost all male) who treat the thrills and chills of high-stakes investing as a kind of competitive sport continue to be very prominent. But many office cubicles are now filled with a different, newer type of personality-the fastidious, idea-filled wonk whose passions in life are mostly quantitative and analytical, particularly involving mathematical manipulations. This is linked to the gradual movement of modern markets toward greater and greater rationality. Over time, markets established to trade commodities, equities, bonds, and financial derivatives tend to become more efficient at setting correct prices. As a result, it becomes harder to uncover fresh information that allows a person to beat the market in the long run. Indeed, in welldeveloped markets it is nearly impossible to make money, over the long run, from simple speculation. Yet so long as humans run them, markets will never be perfectly efficient. Somebody will always discover some small advantage. Increasingly, traders do this by reducing risks (via what they call "hedging"), and mining unexploited buying and selling opportunities exposed by complex mathematical formulas. The problem is that over time, these advantages tend to dissipate. Innovative methods leak into general circulation, or eventually fail in the face of altered behavior among wised-up competitors. The result is that the margins of success tend to get thinner and thinner. Most successful financiers today operate on razorthin profits; they make their millions by uncovering tiny pockets of irrational pricing and then buying and selling in massive volumes to leverage these small profits into substantial sums. This kind of behavior, practiced in many sectors, makes an economy more and more precise and productive. It can also make the unearthers of small economic inefficiencies very rich-putting a premium on the esoteric math and computer skills that requires. Although they have always existed, math geniuses working to rationalize markets have become much more prevalent in recent years. "The nerds are on the rise," says Frank Partnoy, a former derivatives trader who has written a book about the culture of the derivatives industry. "You have the people who were the quarterbacks in high school working side-by-side with the guys who played chess and wrote computer programs. The whole feeling of the industry is different." The new wonks have transformed Wall Street's culture, blurred the lines between academia and finance, and transformed the range of products available to investors. They have also helped create within our finance industry a unique cultural synthesis of the active and practical with the contemplative and theoretical. While across the rest of modern society there is a yawning chasm between the worlds of math and science and the world of social interaction, on Wall Street these two cultures are increasingly fusing. Through most of U.S. history, a good soldier in the investment industry needed strong social skills to attract clients, and steely competitive abilities to see him through jousts with economic opponents. Many traders, bankers, and brokers acquired such skills through the hypercompetitive world of sports. A 1985 survey showed that a full quarter of the male employees at large investment firms had participated in interscholastic athletics on the college level. A social bifurcation often split the finance labor force. Some "white shoe" firms oriented toward wealthy clients sought out employees from Ivy League colleges and the "right" social background. Other companies tended to hire hungry, ambitious strivers from working class origins. "Even today, the typical person you see managing a fund is often the first in his family to go to college. He's worried about status maybe a little more than he should be," says Larry Hite, an enormously successful investment manager of the 1980s. Arbitrary factors have become less and less relevant to Wall Street hiring as the business has become bigger, more competitive, and more complex. Wall Street can't afford to close itself to new talent, because of the relentless discipline financial markets impose on their participants. If you don't make money, you will not continue to participate in the game. So hires are now made mostly on the basis of raw merit. For the salaries they offer, banks and brokerages can often have their pick of America's best students (as well as stars from abroad-Chinese, Indian, Israeli, Eastern European, and other imports have become quite prominent). The growing presence of quantitative nerds on Wall Street began to be noticed around the late 1970s and early 1980s. Peter Bernstein, author of the investing analysis Capital Ideas, traces the shift to the bear market of 1973-1974. After years of steady increases, the stock market entered a tailspin during a severe recession. Brokers had grown lazy and were making money largely by recommending "nifty fifty" stocks of fast-growing companies. When the Nifty Fifty tanked, dozens of marginal players went under. At the same time, the arrival of the first practical business computers, an excess supply of scientists thanks to the end of the Vietnam War, and new mathematical insights from academia, brought a bevy of new technology and manipulative techniques to Wall Street. A larger percentage of the new work force was defined by skills in math, statistics, and computer programming. Advanced degrees other than MBAs were beginning to be seen in large numbers for the first time. Many specialists in previously exotic fields like physics and economic forecasting began to show up. Sometimes all it took to become a hot commodity on Wall Street was one academic thesis on the right subject. "You're seeing the emergence of types of people who, by virtue of some big idea that they present, are getting real recognition. Now they're everwhere," says Charlie Smith, a Queens College sociologist who has written extensively about the cultures of Wall Street. "That's the secret of Bloomberg's success-it's a numbercrunching operation full of physics majors and other quantitative types," business researcher Stephen Malanga tells TAE, referring to the stellar financial-information service that New York City's current mayor ran before he entered politics. Economist Larry Kudlow notes that "Wall Street has always had a deep, intensive interest in number-crunching. So it's not brand new. What is new is that the technology revolution has made it easy, cheap, and quick to carry out. So quantitative virtuosity is now essential to keeping up.' In addition to numbers and computers, many of the new finance wonks seem to have an interest in music. Nearly all of the investment professionals TAE interviewed play an instrument, and almost half have made a recording. Music seems to fit well with investing because it draws on mathematical reasoning, and because performing musicians have learned how to work under pressure and relate to audiences. "The typical gunslinger of the 1960s or '70s has been pushed aside," summarizes Bernstein. "Everyone has to use some quantitative techniques, no matter what he does." At first, the new quantitative players were a mere trickle, but as financial trading traffic has soared in recent years they have poured in as a flood. "There's a certain isolation of the wonks from the old guard. You can often see two groups of people at a company picnic or Christmas party," says Partnoy. "But it's not that it's two separate worlds." The line between pointy-headed academic work and real-world high finance has also become increasingly blurry. One early and relatively simple example is index funds (which assemble stocks from all the companies in a given category, thereby investing not in particular firms but in the overall prosperity of America). Today's single most popular way for individuals in the U.S. to hold stocks, index funds owe their existence to computers and academic research. As stock market historian B. Mark Smith explains, "selfdescribed computer nerd" William Sharpe realized that if one diversified a portfolio widely enough, the intrinsic risks of stocks cancel each other out, leaving only the volatility of the national economy itself as a risk factor. Sharpe published his work (extensions of which eventually won him a Nobel Prize in economics) in 1964. Within the decade, index funds were commercially available to consumers, and within two decades they were one of the country's favorite investments. Today, the Vanguard Group's S&P 500 index fund holds more assets than any other mutual fund. Ideas now flow almost seamlessly between university campuses and trading floors, and academic innovations regularly turn into commercial blockbusters. "You've reached a point where the difference between what my students and I do here and what they want done at Morgan Stanley or wherever is close to nil," says Steven Shreve, who heads Carnegie Mellon University's doctoral program in mathematical finance. "There's a problem we run into frequently with some bit of research which we want to publish and some firm somewhere would rather have as a trade secret." Not only ideas, but bodies and brains more than ever flow between academe and investment companies. "Even in the early 1990s, I could probably name all of the professors who were working on Wall Street," says Bernstein. "Today I can't. There are too many." At Carnegie Mellon, Princeton, Cornell, MIT, and other universities, students even in non-financial disciplines like engineering are increasingly finding their way into finance firms. In 2001, about 5 percent of engineering doctorates were awarded to people doing work in economics. The blurring goes both ways: Some of the new finance players begin to look and act like academic institutions. Algorithmics, a Toronto-based financial risk-management strategy and software firm, publishes its own research journal, and as many as a dozen peer-reviewed mathematical papers each year. "It's a lot like being in a university," says Algorithmics vice president Dan Rosen, a former University of Toronto mathematics researcher. "Except that here we're applying the research we do, and we're doing it right away." New York City-based D. E. Shaw (from which sprang Jeff Bezos and his plan for creating Amazon.com) is described by one employee as "the most luxurious college dorm in all of human history. We are developing these incredibly complex mathematical models. A lot of it is just bull sessions, but the difference is that nearly everyone knows what they are talking about." In addition to changing Wall Street's culture, the new influx of finance wonks has changed the nature of the products sold there. Since nearly all markets become less lucrative as they mature, the biggest profits tend to result from creating a new way of putting money to work. Some markets actually become so efficient that they vanish as profit centers: Chicken egg futures, for example, were a subject of active commodity trading into the mid 1970s, but no longer exist because everyone involved in buying has the same information, and prices don't fluctuate much any more. On the other hand, brand new markets pop up all the time now. New markets can be born on the basis of a single insight. Drexel Burnham Lambert literally invented a new trading market for high-yield bonds in 1977. Previously, any company that missed a payment on a bond would find it almost impossible to sell securities again. And if a smaller company wanted to issue bonds to take over a larger one, buyers could not be found. Then Michael Milken convinced his firm to begin trading higher-risk, high-yield bonds, creating a major industry in the process. While the high-yield bonds Milken pioneered stemmed from a reasonably simple intellectual insight, other innovative new investments grow out of abstruse technology or complex mathematics. "There is a new emphasis on creativity," says David Harris, a partner in Drexel Burnham's Houston office during the firm's heyday. "You act as a combination of evangelist and educator. You have to think for yourself every minute." It would be easy to overstate the influence of nerdy academics on Wall Street. With the major exception of the wholly computerized NASDAQ market, nearly all of the important exchanges for stocks, bonds, and commodities still operate trading floors where humans make the final investment decisions. Managers at any fund must often override their technical models. "You can have quantitative work up the wazoo to inform people in every way," says Mitch Abolafia, a professor at the State University of New York-Albany who has studied the culture of trading floors. "But, in the end, it's still humans making the final decisions." Humans continue to outdo computers in many aspects of the business. In the early 1990s, nearly everyone believed that the New York Stock Exchange would eliminate the stock specialists who match buyers with sellers on the trading floor. A combination of academic research and real-life experience, however, showed that human traders were more efficient in many respects. It is likely that they will still exist 100 years from now. There are good reasons for people to remain leary about letting mathematical formulas, computerized decision making, and academic theory take over entirely. Even the most brilliant experts remain fallible. Long Term Capital Management was a giant, hotshot, well-financed, and heavily quantitative fund for very wealthy investors. It included not one but two Nobel laureates on its staff, and was built on pristine financial insights from leading edge research. In 1998, the firm collapsed with enormous losses, and could have taken dozens of big companies with it had the New York Federal Reserve not intervened. Theoretical models of finance are like weather forecasts: Even the most fully developed models, run on super-powerful computers, can't effectively aggregate all the information that can affect the value of an investment. A veteran trader commands experiential wisdom and common sense that no academic method has been able to replace. In a classic 1959 lecture, "The Two Cultures," British academic C. P. Snow describes a yawning disconnect between academics in the sciences and those operating in the humanities: scholars of literature who cannot describe the laws of thermodynamics, and scientists ignorant of Shakespeare. The two groups actually speak different languages, creating jagged schisms in intellectual life. A similar schism might well have emerged on Wall Street. Had the unimaginative stock pickers of the 1970s remained in the saddle, it's hard to imagine that many of today's pacesetters in finance would have been lured away from the shorter hours, vastly lower stress, and comfortable tenuretrack jobs of academia. Our financiers could have remained in their ruts; competitors in London might have taken the world lead in innovation and volume; and America would have been much poorer for the difference. Financial Futurist? .Robin Hanson is a jittery, intense, George Mason University economics professor. Even as a small child he spent lots of time wrapped up in his own mind. His father worked as a preacher and IRS agent, and eventually settled down into a career as a computer programmer. His mother taught school, worked for a finance firm, and now illustrates children's books. "I was a really self-absorbed loner," he says. .A good science student, he majored in physics in college. During his freshman year, he began a severalyear effort to make graphs of just about every aspect of the world around him. "I'd have one axis which showed the size of things and another which showed their mass," he explains. "It seemed like a good idea." He went on only a handful of dates, avoided most extra-curricular activities, and had few friends. .Eventually, Hanson took jobs at Lockheed and then NASA, researching artificial intelligence and statistics. He helped develop the Cassini mission to Saturn, using the most complex robotic spacecraft ever built. While auditing classes at Stanford, he worked on the Xanadu project, a collaborative computer experiment that presaged the World Wide Web. .In 1999 Hanson earned a Ph.D. in economics, and today he promotes many controversial free market ideas. He'd like to improve medical care, for instance, by making insurance providers pay large penalties if patients die. His biggest proposal is to use something called "idea futures" to remake the world's financial industries. .Idea futures are betting markets similar to those that bookies run on sporting events, except they would consider serious questions like the potential effectiveness of a new cancer treatment, or a company's likelihood of producing a certain level of earnings. Rather than making decisions by committee or individual fiat, Hanson suggests, corporations, governments, and even individuals could make decisions by sampling market odds. .His proposals grow out of economists' discovery over the past 40 years that prices aggregate an amazing amount of useful information-more, indeed, than any human expert could ever take into account. Although current American laws ban idea futures as a form of gambling (even in Nevada), they have proven effective in real world tests. The Iowa Electronic Markets (which have a special federal exemption) let participants place real-money bets on the fate of political candidates. It turns out that they predict election outcomes better than opinion polls. The Hollywood Stock Exchange, a massive play-money market for entertainment ideas, often does a better job of forecasting movie grosses than the complex economic models used by the studios who film them. .Hanson suggests legal idea-betting markets could allow companies to easily and effectively test new strategies, do market research, and decide the fates of their managers. He would like to see idea futures become not just a centerpiece of investing and finance, but an all-encompassing way of organizing the world. He's even circulated a working paper suggesting that they be used as the basis for public policy decisions. "You could have a heads-up computer display that would let you participate in a betting market as to which restaurant you should pick to eat lunch in," he comments casually, his own head firmly in the clouds. Instead, Wall Street and academia began to cross-fertilize. The smooth salesmen and driving competitors of the Street's previous generation became much more mathematical. Bright individuals who might have retreated behind college walls became more practical and sociable. A bridge went up between the two cultures. By helping to root out inefficiencies, finding new ways to recombine money, and developing fresh analytical techniques, the new finance wonks helped America's capital markets remain the most productive, rational, and innovative in the world. Even as we write, a surge of fresh new ideas continues to flow through our brokerages, banks, and exchanges, nurturing new markets and keeping older ones strong. So did a rather pale and retiring collection of brainy young individuals help keep America's entrepreneurial muscles bulging. Eli Lehrer is a TAE senior editor. Karl Zinsmeister is the magazine's editor in chief.