Fortune's Formula (16 page)

A
FTER SHE DIVORCED
Claude Shannon, Norma Levor moved to Hollywood and joined the Communist Party. Claude did not see her for over twenty years. Norma and her second husband, Ben Barzman, were blacklisted screenwriters during the McCarthy era. When it appeared that the U.S. government would force them to name fellow Communists or face prison, they fled the country for France.

In 1963 Norma visited Cambridge to help her daughter furnish a Harvard summer school dorm room. Norma took the initiative of contacting Shannon.

They met at the Commander Hotel bar and compared lives. “I have a nice wife, wonderful kids,” Claude told her. “I teach, do research. I have a collection of twenty-three cars. I tinker.”

At the word “tinker,” he laughed in spite of himself. Norma put out her hand. Claude took it and kissed her palm.

They went up to Norma’s room and made love. Afterward, Claude asked, “Are you happy?”

“Reasonably. And you?”

“Reasonably.”

Shannon told Norma that their marriage would have been doomed in any case: her radical politics would not have mixed with his secret cryptographic work. No less an odd match was communism and Shannon’s latest research interest, the stock market.

Shannon’s attitude toward money was an enigma to the people around him. Growing up in Michigan, he never wanted for necessities, nor had much of a chance to spend a dollar foolishly. As a graduate student, Shannon was “entirely without funds,” as Vannevar Bush wrote.

This changed with his first marriage. Norma’s wealthy mother hired a decorator and furnished the Shannons’ modest Princeton apartment with smart modern furniture. Claude never felt comfortable with the makeover, said Norma, complaining that it was like living in a stage set.

It was Betty who nudged Claude toward an interest in investments. Before his second marriage, Shannon kept his life savings in a checking account, earning no interest. Betty suggested that it might be a good idea to put some money in bonds—or stocks, even.

The adult Shannon cultivated the image of a disinterested seeker of truth, disdaining the values of the marketplace. “I’ve always pursued my interests,” he told one journalist, “without much regard for financial value or value to the world.” “When he was working on a theory,” explained Betty, “he was thinking of things that were beautiful mathematically.” Having solved the abstract problem that interested him, he was ready to move on. “Once he was done with something,” Betty said, “he was done with it.” Claude admitted what was clear to anyone who ever laid eyes on the Toy Room: “I’ve spent lots of time on totally useless things.”

Stories tell of Shannon’s otherworldly indifference to money. Bell Labs long had a policy of keeping salaries secret. In 1955 a biophysicist named Bob Shulman made a list of a hundred employees and went to each with an irresistible offer. Put
your
salary on this list, Shulman said, and I’ll let you see everyone else’s. Most of the hundred accepted, among them Shannon. The list revealed that Shannon was making no more than a lot of other people of no great reputation. Bell Labs was sufficiently shamed to give Shannon a 50 percent raise.

A colleague who borrowed Shannon’s MIT office while he was away found a large uncashed check made out to Shannon. It was a year old. This incident appears to be the grain of truth behind an MIT legend of piles of uncashed checks languishing in Shannon’s office.

In the late 1950s, Shannon began an intensive study of the stock market that was motivated both by intellectual curiosity and desire for gain. He filled three library shelves with something like a hundred books on economics and investing. The titles included Adam Smith’s
The Wealth of Nations
, John von Neumann and Oskar Morgenstern’s
Theory of Games and Economic Behavior
, and Paul Samuelson’s
Economics
, as well as books with a more practical focus on investment. One book Shannon singled out as a favorite was Fred Schwed’s wry classic,
Where Are the Customers’ Yachts?

At the time he was designing the roulette computer with Thorp, Shannon kept notes in an MIT notebook. Part of the notebook is devoted to the roulette device and part to a wildly disconnected set of stock market musings. Shannon wondered about the statistical structure of the market’s random walk and whether information theory could provide useful insights. He mentions such diverse names as Bachelier, (Benjamin) Graham and (David) Dodd, (John) Magee, A. W. Jones, (Oskar) Morgenstern, and (Benoit) Mandelbrot. He considered margin trading and short-selling; stop-loss orders and the effects of market panics; capital gains taxes and transaction costs. Shannon graphs short interest in Litton Industries (shorted shares vs. price: the values jump all over with no evident pattern). He notes such success stories as Bernard Baruch, the Lone Wolf, who ran about $10,000 into a million in about ten years, and Hetty Green, the Witch of Wall Street, who ran a million into a hundred million in thirty years.

Shannon once went into the office of MIT grad student Len Kleinrock to borrow a book. (Kleinrock would later have a measure of fame for his role in starting up the great wire service of our age, the Internet.) The book Shannon wanted to borrow contained tables of wealth distribution in the United States. It told how many millionaires there are, how many people with a net worth of $100,000, and so on. Puzzled, Kleinrock asked Shannon what he needed it for. Shannon said he was devising a system for investing in the stock market.

Still puzzled, Kleinrock asked, “You’re interested in making
money
in the stock market?”

“Yes, aren’t you?” Shannon replied.

When friends tactfully asked Shannon what he was doing with his time, he would often speak of using mathematical methods to invest in the stock market. It was rumored that Shannon
had
made a lot of money through his investments. Not everyone took these stories at face value. “Usually in my experience the very few who somehow develop a knack for risk-corrected excess total return do become rich very quickly and do reveal that in their observable life style,” Paul Samuelson told me. “I do not remember any gossip at the MIT watercoolers that the Shannons had levitated out of the academic class.”

Others suspected that the talk of a stock market “killing” was an excuse for dropping out of the scientific world. “You weren’t affected by your success in the stock market, were you, taking away the necessity to work so hard?” asked journalist Anthony Liversidge in a 1986 interview. Shannon’s answer was “Certainly not.” He continued,

Despite the fact that he never published a word on the subject, the stock market became one of the great enthusiasms of Claude Shannon’s life, and of Betty’s as well. Soviet mathematician Boris Tsybakov recalls a 1969 visit to America in which Shannon flew off into an enthusiastic tangent, outlining market theories on napkins at the MIT faculty club. Shannon apologized for the fact that Tsybakov would not be able to put these ideas into practice in the Soviet Union.

Shannon was not the first great scientific mind to suppose that his talents extended to the stock market. Carl Friedrich Gauss, often rated the greatest mathematician of all time, played the market. On a salary of 1,000 thalers a year, Euler left an estate of 170,587 thalers in cash and securities. Nothing is known of Gauss’s investment methods.

On the other hand, Isaac Newton lost some 20,000 pounds investing in the South Sea Trading Company. Newton’s loss would be something like $3.6 million in today’s terms. Said Newton: “I can calculate the motions of heavenly bodies, but not the madness of people.”

Shannon told one of his Ph.D. students, Henry Ernst, that the way to make money in the market was through
arbitrage
. That term was in the process of being redefined by the information age.

Originally it referred to a scheme for profiting from small price differences between geographically remote markets. Gilded Age financier Jay Gould discovered that the price of gold varied slightly between London and New York. Gould bought gold wherever it was cheaper and shipped it to wherever it was more expensive, selling it for a quick profit.

Instantaneous electronic communication has mostly erased geographic price disparities. Today “arbitrage” is used to describe almost any attempt to profit from irrationality in the market. Much like Gould, today’s arbitrageurs usually buy
and
sell nearly the same thing at nearly the same time in order to make a profit. Because arbitrage profits can be quick, the return on investment may be far more than with more conventional stock or bond investing.

“Arbitrage” is a charged word. Those of leftish political convictions often see arbitrage as money for nothing, the epitome of Wall Street “greed” and fortunes made while providing little or no visible social benefit. To efficient market theorists, arbitrage is perhaps no less an affront. By definition, arbitrage opportunities cannot exist in an efficient market. The strongly theoretical slant of much academic finance is well illustrated by the adoption of “no arbitrage” as an axiom. Financial “theorems” are proved with Euclidean rigor by assuming that no arbitrage opportunities exist.

This circular logic has given rise to a joke. An MIT (University of Chicago) economist says there’s no point in looking for hundred-dollar bills in the street. Why? Because,
were
there any hundred-dollar bills, someone would already have picked them up.

This is not quite the paradox it appears. Whether there are hundred-dollar bills in the street depends on how frequently people drop them and how quickly other people pick them up. The efficient market theorists claim that picking up is easy. There is a race between the picker-uppers to snatch up the bills before anyone else does. This competition promptly clears the streets of hundred-dollar bills. The free money vanishes like snowflakes on a hot griddle. One may then say, to good approximation, that there is no free money lying around.

The critics of the efficient market hypothesis make a more modest case, that
sometimes
people drop bills faster than the picker-uppers collect them. In some places, the hundred-dollar bills remain on the street for a while.

Shannon apparently saw the Kelly formula as the mathematical essence of arbitrage. In the spring term of 1956, Shannon gave a class at MIT called Seminar on Information Theory. One lecture was titled “The Portfolio Problem.” The lecture is documented only by a mimeographed lecture handout saved by student W. Wesley Peterson (now a prominent information theorist) and housed with Shannon’s papers at the Library of Congress.

This handout would mystify anyone looking for investing advice. The lecture is on John Kelly’s gambling system. It mentions
The $64,000 Question
and a wire service giving horse tips. Aside from the title, it does
not
mention portfolios or the stock market.

Presumably, Shannon made the connection in the lecture itself. His point was that a horse race is like a particularly fast-paced and
vicious
stock market. It would be alarming to visit a great stock exchange and find the floor littered with worthless stock certificates. Try visiting a racetrack. Most wager tickets become worthless within minutes.

It is folly to bet everything on a favorite (horse or stock). The only way to survive is through diversification. Someone who bets on every horse—or buys an index fund—will at least enjoy average returns, minus transaction costs. “Average” isn’t so hot at the racetrack, given those steep track takes. “Average” is pretty decent for stocks, something like 6 percent above the inflation rate. For a buy-and-hold investor, commissions and taxes are small.

Shannon was more interested in above average returns. The only way to beat the market (of stocks or horse wagers) is by knowing something that other people don’t. The stock ticker is like the tote board. It gives the public odds. A trader who wants to beat the market must have an edge, a more accurate view of what bets on stocks are really worth.

There are of course many differences between a racetrack and a stock exchange. A horse must win, place, show, or finish out of the money: those are the only distinct outcomes. For stocks and other securities, the range of outcomes is a continuum. A stock can rise or fall by any amount. It may pay dividends, split, or merge. Time at the track is divided into discrete races. Time in the market is continuous. An investor can stay invested for as long or short a time as desired.