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Are Stock Prices Predictable?
It is doubtful.
Paul Samuelson, economist and Nobel laureate, once remarked that it is not easy to get rich in Las Vegas, at Churchill Downs, or at the local Merrill Lynch office. All investors, professionals as well as amateurs, acknowledge the truth of this observation. Even smart people have a hard time getting rich by predicting stock prices.
Some people never try to outguess the market: they simply hang on to the stocks they inherited, bought long ago, or acquired in some employer-sponsored savings program. Others buy and hold under the conviction that trading finances yachts only for brokers, not for customers.
Yet, in the face of admittedly high odds, enough people do try to predict stock prices to keep an entire industry humming. The demand for the wisdom produced by armies of security analysts, portfolio managers, television pundits, software peddlers, and newspaper columnists shows no sign of waning. Some of the wealthiest people on Wall Street are professionals whose bank accounts have been inflated by a constant flow of investment advisory fees. I have already pointed out that the number of investmentmanagement organizations tripled just during the 1980s. Forbes, Barron's, and The Wall Street Journal have subscribers that number in the millions. Index funds, which hold a diversified cross-section of the market and never sell one stock in order to buy another, account for less than 15 percent of all equity portfolios.
This appetite for predicting stock prices is all the more striking, because a huge volume of academic research demonstrates that it is a devilishly difficult job not likely to get any easier. While no one goes so far as to say that it is impossible to make good predictions or that all predictions are destined to be wrong, the abundant: evidence and the robust character of the theories that explain the evidence confirm that the task of predicting stock prices is formidable by any measure.
The exploration into whether investors can successfully forecast stock prices has roots that reach all the way back to 1900, when Louis Bachelier, a young French mathematician, completed his dissertation for the degree of Doctor of Mathematical Sciences at the Sorbonne. The title of the dissertation was "The Theory of Speculation." This extraordinary piece of work, some seventy pages long, was the first effort ever to employ theory, including mathematical techniques, to explain why the stock market behaves as it does. Bachelier supported his novel theoretical analysis with a sophisticated study of the French capital markets at the turn of the century.
It is worth noting that Bachelier was an academic all the way. He employed his profound understanding of the markets for his intellectual exercise: we have no evidence that he ever speculated or invested in the markets he was analyzing. He set the style for many later theorists who, like him, refrained from putting their money where their minds were.
Bachelier was far ahead of his time. Paul Cootner, one of the leading finance scholars of the 1960s, once delivered this accolade: "So outstanding is his work that we can say that the study of speculative prices has its moment of glory at its moment of conception."
Bachelier laid the groundwork on which later mathematicians constructed a full-fledged theory of probability. He derived a formula that anticipated Einstein's research into the behavior of particles subject to random shocks in space. And he developed the now universally used concept of stochastic processes, the analysis of random movements among statistical variables. Moreover, he made the first theoretical attempt to value such financial instruments as options and futures, which had active markets even in 1900. And he did all this in an effort to explain why prices in capital markets are impossible to predict!
Bachelier's opening paragraphs contain observations about "fluctuations on the Exchange" that could have been written today. He recognizes that market movements are difficult to explain, even after the fact, and that they often generate a self-reinforcing momentum:
Past, present, and even discounted future events are reflected in market price, but often show no apparent relation to price changes....[A]rtificial causes also intervene: the Exchange reacts on itself, and the current fluctuation is a function, not only of the previous fluctuations, but also of the current state. The determination of these fluctuations depends on an infinite number of factors; it is, therefore, impossible to aspire to mathematical predictions of it....[T]he dynamics of the Exchange will never be an exact science.
Despite these demurrers, Bachelier sets himself an ambitious goal: to offer "a formula which expresses the likelihood of a market fluctuation" -- that is, a move upward or downward in stock prices. Recognizing that fluctuations over time are virtually impossible to interpret, he begins by concentrating on the market at a given instant, promising to establish "the law of probability of price changes consistent with the market at that instant. This approach leads him into more profound investigations: the theory of probability and the analysis of particles in space subject to random shocks.
In view of the originality and brilliance of Bachelier's analysis of financial markets, we might expect him to have been a man of stature in his own time. It is easy to picture him as an inspiring professor at the Sorbonne, or perhaps lured from France to Harvard or Oxford. We can note his large following of students, who, having gleaned so much wisdom, will go on to make their own mark in the study of finance, uncertainty, and random behavior. Or perhaps we can visualize him as a fabulously successful investor, a forerunner of Keynes, combining financial acumen with theoretical innovation.
The truth is far different. Bachelier was a frustrated unknown in his own time. When he presented his dissertation to the committee at the Sorbonne, they awarded it merely "mention honorable," a notch below the "mention très honorable" that was essential for anyone hoping to find a job in the academic world. It was long time before Bachelier finally won an appointment, and even then it was only at the provincial university at Besancon. Besancon is about as provincial as provincial France can get.
Some of the difficulty seems to have stemmed from a mathematical error in a paper he published in 1913 -- a slip that haunted him for many years. As late as 1929, when he applied for a position at the University at Geneva, a Professor Gevrey was still scandalized by the error, and, after consulting Paul Lévy, another expert in the field, Gevry had Bachelier blackballed from the University. Lévy later recognized the value of Bachelier's pioneering work, and the two became reconciled.
Bachelier's real problem, however, was that he had chosen an odd topic for his dissertation. He was convinced that the financial markets were a rich source of data for mathematicians and students of probability. Twenty years after writing his dissertation, he remarked that his analysis had embodied "images taken from natural phenomena...a strange and unexpected linkage and a starting point for great progress." His superiors did not agree. Although Poincaré, his teacher, wrote that "M. Bachelier has evidenced an original and precise mind," he also observed that "The topic is somewhat remote from those our candidates are in the habit of treating."
Benoit Mandelbrot, the pioneer of fractal geometry and one of Bachelier's great admirers, recently suggested that no one knew where to pigeonhole Bachelier's findings. There was no ready means to retrieve them, assuming that someone wanted to. Sixty years were to pass before anyone took the slightest notice of his work.
The key to Bachelier's insight is his observation, expressed in a notably modern manner, that "contradictory opinions concerning [market] changes diverge so much that at the same instant buyers believe in a price increase and sellers believe in a price decrease." Convinced that there is no basis for believing that -- on the average -- either sellers or buyers consistently know any more about the future than the other, he arrived at an astonishing conjecture: "It seems that the market, the aggregate of speculators, at a given instant can believe in neither a market rise nor a market fall, since, for each quoted price, there are as many buyers as sellers." (emphasis added)
The fond hopes of home buyers in California during the 1980s provide a vivid example of Bachelier's perception. Those buyers were willing to pay higher and higher prices for houses "because values could only go up." This myopic view implied that the people who were selling the houses were systematically ignorant or foolish. Clearly they were not.
Prices in markets that deal in bets on the future are, at any given instant, as likely to rise as they are to fall -- as California real-estate prices have demonstrated. That means that a speculator has an equal chance of winning or losing at each moment in time. Now comes the real punch, in Bachelier's words and with his own emphasis: "The mathematical expectation of the speculator is zero." He describes this condition as a "fair game."
Here Bachelier is not just playing a logical trick by setting unrealistic assumptions so tightly that no other result is possible. He knows too much about the marketplace to resort to something that deceitful. In a disarmingly simple but perceptive statement about the nature of security markets, he sums up his case: The probability of a rise in price at any moment is the same as the probability of a fall in price, because "Clearly the price considered most likely by the market is the true current price: if the market judged otherwise, it would quote not this price, but another price higher or lower."
Under these conditions, prices will move, in either direction, only when the market has reason to change its mind about what the "price considered most likely" is going to be. But no one knows which way the market will jump when it changes its mind; hence the probabilities are 50 percent for a rise and 50 percent for a fall.
This conclusion led Bachelier to another important insight. The size of a market fluctuation tends to grow larger as the time horizon stretches out. In the course of a minute, fluctuations will be small -- less than a point in most instances. During a full day's trading, moves of a full point are not unusual. As the time horizon moves from a day to a week to a month to a year and then to a series of years, the range within which prices swing back and forth will grow ever wider.
But how rapidly will the range expand? Bachelier answered that question with a set of mathematical equations demonstrating that "this interval [will be] proportional to the square root of time." This prediction has held up with stunning precision.
Stock prices in the United States over the past sixty-odd years have behaved almost exactly as Bachelier said they would. Two-thirds of the time, they have moved within a range of 5.9 percent on either side of their average level in the course of a month. But the range in the course of a year has not been 72 percent, or twelve times as much: rather, it has averaged around 20 percent, or about three and a half times the monthly range. The square root of 12 is 3.46!
If stock prices vary according to the square root of time, they bear a remarkable resemblance to molecules randomly colliding with one another as they move in space. An English physicist named Robert Brown discovered this phenomenon early in the nineteenth century, and it is generally known as Brownian motion. Brownian motion was a critical ingredient of Einstein's theory of the atom. The mathematical formula that describes this phenomenon was one of Bachelier's crowning achievements.
Over time, in the literature on finance, Brownian motion came to be called the random walk, which someone once described as the path a drunk might follow at night in the light of a lamppost. No one knows who first used this expression, but it became increasingly familiar among academics during the 1960s, much to the annoyance of financial practitioners. Eugene Fama of the University of Chicago, one of the first and most enthusiastic proponents of the concept, tells me that random walk "is an ancient statistical term; nobody alive can claim it." In later years, the primary focus of research on capital markets was on determining whether or not the random walk is a valid description of security price movements.
Bachelier himself, hardly a modest man, ended his dissertation with this flat statement- "It is evident that the present theory resolves the majority of problems in the study of speculation by the calculus of probability."
Despite its importance, Bachelier's thesis was lost until it was rediscovered quite by accident in the 1950s by Jimmie Savage, a mathematical statistician at Chicago. Savage himself is worth a story. Milton Friedman, after associating with Savage for twenty years, described him as "...one of the few really creative people I have met in the course of my intellectual life....Here is one of those extraordinary people of whom there are only a handful in any university at any time."
Savage's parents delayed in giving him a first name because his mother was seriously ill when he was born in 1917. They later named him Leonard, but a nurse in the hospital had called him Jimmie and entered that name in the hospital records. Many years later, Savage arranged for a court order to make it official: His name became Leonard Jimmie Savage.
A child prodigy, Savage was afflicted with poor eyesight -- he once confessed that "my eyes are too weak for much mischief." When attending a public lecture, he was wont to walk up to the platform, examining the equations on the blackboard with a highpowered glass that he carried for the purpose. He once described himself this way: "I am a man of very many words. If I were to speak extemporaneously, I could probably hold myself spellbound for an hour."
Perhaps he was right to be spellbound: In the course of an outstanding career in various applied and theoretical areas of mathematics, Savage was offered faculty appointments by major universities in departments of biology, economics, management, and physics, in addition to mathematics.
Some time around 1954, while rummaging through a university library, Savage chanced upon a small book by Bachelier, published in 1914, on speculation and investment. Fascinated, he sent postcards to his economist friends, asking "Ever heard of this guy?" Paul Samuelson, who was just then beginning to explore theories of market behavior and valuation on his own, could not find the book in the MIT library, but he did discover a copy of Bachelier's Ph.D. thesis. Samuelson has remarked that "Bachelier seems to have had something of a one-track mind. But what a track!" He immediately recognized the quality of Bachelier's work and spread the word throughout the economics profession. Bachelier's influence is apparent in Samuelson's early treatment of the behavior of speculative prices.
Even if Bachelier had been better known in his lifetime, few people would have paid much attention to what he had to say. Those who controlled the real world of finance in the United States had little interest in the inner workings of the stock market. Playing the market was just too much fun. Stock prices rose 60 percent from 1900 to 1916, declining in only four of those years. From 1921 to 1929, as the American industrial juggernaut linked itself to the nation's farms through the rapidly expanding railroad system, stock prices soared sixfold.
By 1900, Thomas Edison's stock tickers had been punching out prices for nearly thirty years. The streets of the financial district swarmed all day, and often into the night, with young boys rushing to deliver the latest news bulletins.
For many years those bulletins were inscribed by hand with a stylus on a sheaf of tissue and carbon paper that produced up to 24 copies at a time. Until the introduction of small, hand-cranked printing presses in the mid-1880s and then the Dow, Jones news ticker in 1897, these handwritten bulletins were the main source of information for Wall Street traders and investors. Dow, Jones & Co. continued to deliver bulletins by messenger up to the end of World War II.
Recipes for predicting stock prices were in urgent demand on Wall Street throughout these years. By far the most famous was the Dow Theory, developed by Charles Dow, co-founder of Dow, Jones & Co. in 1882 and the first editor of the company's flagship publication, The Wall Street Journal, launched in 1889.
Dow was born in a small town in Connecticut in 1851. He had had twenty jobs before he found his real love in journalism when he went to work as a reporter and part-time printer at the Springfield (Massachusetts) Republican in 1869. The editor, Samuel Bowles, a brilliant though difficult man, was one of the first editors to insist that the lead paragraph of an article should tell the whole story in brief: "who, what, when, where, and why."
In 1875, Dow left Springfield to join the Providence Journal, where he attracted national attention with a series of articles on the history of steam transportation. In those articles he concentrated on the efforts of the sailing freighters to withstand the inroads of the steamboat companies, many of which were forming joint ventures with the expanding railroad system.
In 1879, a group of eastern financiers, along with Senator Jerome Bonaparte Chaffee of Colorado, invited Dow to join them on a visit to Leadville, Colorado, the site of a huge silver strike. One of the mines, the Camp Bird mine, had been discovered by three Gallagher brothers -- Irish laborers who on their arrival in Leadville had been refused credit for a few loaves of bread. The town had a population of 18,000 when Dow arrived; two years earlier, before the Gallaghers arrived on the scene, the mining camp had consisted of nothing but tents. There were numerous hotels and establishments when Dow arrived. And there were dancing houses where ladies charged 50 cents for a set of dances. In Dow's words, those ladies had "descended to the very root of the soiled ladder."
After three months, the Easterners had had enough. Dow's last article from Leadville to the Providence Journal quoted one member of the party, about to down a last glass of beer, who said, "Be it ever so humble, there's no place like Fifth Avenue."
Dow returned home convinced that the economic future of America was almost unlimited. His experience in the mining country endowed him with an optimistic spirit that he never abandoned.
Deciding that Providence was now too small a town for him, Dow moved to New York City with an old newspaper friend, Eddie Jones. Lloyd Wendt, the historian of Dow, Jones & Co., describes Jones as "a tall, lean, red-haired man with smiling blue eyes and a dimpled chin," far more extroverted and sociable than Dow. Dow also was tall and thin, but he had dark eyes and a full black beard. Slow to anger, he was a man of few words.
The two young men soon found positions at Kiernan's at 2 Broad Street, close to the site where the New York Stock Exchange would open its doors many years later. Kiernan, one of the publishers of the tissue-and-carbon news bulletins, owed his success to his friendship with many of the major players in Wall Street.
Kiernan was delighted to hire Dow and Jones. Jones had a nose lot news and, according to Wendt, could read and understand a financial report faster than anyone else. Dow wrote the news bulletins with skill and clarity. He wanted to write a more analytical daily report as well, but Kiernan was not interested.
Dow, Jones, and a friend named Charles Milford Bergstrasser soon decided to go into the news-distributing business themselves. Bergstrasser, small, gregarious, and excitable, was working for Drexel, Morgan & Company, a banking house. Deciding that Bergstrasser's name was less than euphonious, they called their new company Dow, Jones & Co. (the comma did not disappear for almost fifty years). They opened for business in November 1882 at 15 Wall Street, down wooden stairs to a small, unpainted room next to a soda-water establishment.
Two years later they acquired their first hand-cranked printing press. By 1887, the company had grown so large that clients were complaining that deliveries were too slow and competitors were getting a jump on them. The partners responded by installing an electronic news ticker. Now known as "the broad tape," such tickers are still used on Wall Street.
Early in 1885, Dow, Jones converted its Afternoon News Letter into The Wall Street Journal, whose format and coverage have changed little over the years. As editor for thirteen years, Dow seldom missed writing the paper's daily editorial until his death in 1902. In his commentaries Dow expressed his ideas about the stock market and economic conditions and provided an original, sophisticated analysis of the business cycle, a field of study then in its infancy.
At heart Dow was a scholar rather than a speculator. He was more interested in interpreting the history of the stock market than in devising a system for predicting its future. The world has read his interpretation otherwise.
Underlying the so-called Dow Theory is the assumption that trends in stock prices, once under way, will tend to persist until the market itself sends out a signal that these trends are about to It)se their momentum and go into reverse. Dow's best-known statement on the subject appeared in a Journal article in 1901:
A person watching the tide coming in and who wishes to know the exact spot which marks the high tide, sets a stick in the sand at the points reached by the incoming waves until the stick reaches a position where the waves do not come up to it, and finally recede enough to show that the tide has turned.
This method holds good in watching and determining the flood tide of the stock market....The price-waves, like those of the sea, do not recede at once from the top. The force which moves them checks the inflow gradually and time elapses before it can be told with certainty whether the title has been seen or not.
Recognizing turns in the tide is less simple on Wall Street than it is on the beach. The market does fluctuate. Dow theorists boast that they can identify the very moment when what appears to be only a slight fluctuation is actually the first sign of the reversal of a major trend. They do not always agree among themselves, however. Disputes often arise over whether a slight fluctuation away from a trend is just a temporary setback -- a "correction," in market patois -- or the onset of a new trend. Sometimes the signal appears so late that the main trend has almost exhausted itself, and stock prices are about ready to turn around and start a new trend headed in the other direction.
Even people who have never heard of the Dow Theory are familiar with the Dow Jones Averages, Charles Dow's most lasting contribution to finance. This was the first attempt to create some sort of aggregate indicator of stock-market trends. Although other averages have since appeared, notably those from the Associated Press, the New York Times, and Standard & Poor's, the Dow Jones Averages are still what most people turn to when they want to know "How's the market doing?"
The first Dow Jones Average appeared in the Afternoon News Letter on July 3, 1884. It consisted of the closing prices of eleven companies, nine railroads and two industrials. Dow's idea was to provide an overall measure of the performance of active companies, at a time when an average day's activity on the New York Stock Exchange was about 250,000 shares. Although today's average volume is over 100,000,000 shares a day, 250,000 shares represented at the time a higher level of activity relative to the number of shares listed on the Stock Exchange and available for trading.
In 1882, Dow predicted that "The industrial market is destined to be the great speculative market of the United States." He recognized that his list of companies would change as time passed. After twelve years of constant revision of the composition of the Dow Jones Average, he published the first strictly industrial list on May 26, 1896.
Of twelve industrials included in that list, only one still appears in the Industrial Average: General Electric. The other eleven were American Cotton Oil, American Sugar, American Tobacco, Chicago Gas, Distilling and Cattle Feeding, Laclede Gas, National Lead, North American, Tennessee Coal & Iron, US Leather preferred, and US Rubber. Later listings included such diverse items as Victor Talking Machine, Famous Players Lasky, and Baldwin Locomotive.
The twelve stocks in the first industrial list included all the industrial companies then traded on the New York Stock Exchange. The other companies listed consisted of fifty-three railroads and six utilities. Shares of banks and insurance companies then traded over-the-counter rather than on the floor of the New York Stock Exchange.
The term "industrial" is really a misnomer, because not all of the companies listed as industrials were industrial companies. They were simply all the companies that were neither railroads nor utilities. Dow Jones published separate averages for the railroads and the utilities.
The sparseness of industrials relative to rails in the list is evidence of the boldness of Dow's foresight about the industrial market, as well as an indication of the importance of railroads to the American economy in the late nineteenth century. It reflects something else as well: Most industrial companies did not need as much capital as the rails, which required huge financing for their rolling stock and right-of-way.
In those days, industrial companies tended to rely on a combination of debt and their founders' wealth to finance their growth. This was partly a matter of choice, as incorporation did not offer major benefits to owners at that time. But it was partly because, as one historian of the period has noted, "the securities of industrial corporations were regarded as peculiar, unstable, and speculative. Even the largest and most visible firms were not 'public' corporations." For example, two industrial giants of the period, the Singer Manufacturing Company and McCormick Harvesting Machine (later International Harvester), were still closely held corporations.
Dow died at his home in Brooklyn in 1902, just nine months after Dow, Jones & Co. had been sold to Clarence Barron for $130,000 -- only $2,000,000 in today's purchasing power. About a year later, Samuel Nelson, publisher of Nelson's Wall Street Library, published several of Dow's editorials in a book called The ABC of Speculation. Nelson is believed to be the first to use the expression "Dow Theory." Dow himself never used it.
In 1903, William Peter Hamilton took over as editor of The Wall Street Journal. Hamilton was a Scottish journalist who had joined the paper as a reporter in 1899, while Dow was still there. As editor, he followed Dow's practice of writing almost all the daily editorials himself and continued to do so until his death in December 1929.
Hamilton repeatedly stressed a central idea of Dow Theory that prices on the New York Stock Exchange are "sufficient in themselves" to reveal everything worth knowing about business conditions. Here Hamilton was anticipating a radical concept that was to appear long after his death. In the 1960s, a group of college professors would develop the Efficient Market Hypothesis, based on the notion that stock prices reflect all available information about individual companies and about the economy as a whole. The Efficient Market Hypothesis, however, also looks back to Bachelier, for it assumes that information is so rapidly reflected in stock prices that no single investor can consistently know more than the market as a whole knows. Hamilton, on the contrary, believed that the market itself revealed what stock prices would do in the future.
On October 21, 1929, just before he died, Hamilton predicted the end of the bull market of the 1920s in an editorial titled "The Turn in the Tide," a title that recalled Dow's view of market behavior. Hamilton had made similar predictions of impending disaster in January 1927, June 1928, and July 1928. So "The Turn in the Tide" was a lucky call. The worst day in the history of the Stock Exchange occurred just four days later. In the days ahead, values were to fall 90 percent from their 1929 peak before hitting bottom in 1932.
One of the victims of the crash was Alfred Cowles 3rd, a wealthy man whose father and grandfather had been major stockholders and executives of the Chicago Tribune Company. He was born in Chicago in 1891 and, following family tradition, attended Yale. He graduated in the class of 1913 and went to work as a reporter for the Tribune in Spokane.
Suddenly Cowles came down with tuberculosis. His family shipped him off to Colorado Springs for treatment, which, according to Cowles, "consisted mostly of resting in bed and hoping for the best." The cure, uncertain as it may have been, ultimately succeeded. After ten years in Colorado Springs, he rejoined his family in Chicago. He was 93 years old when he died in 1985.
An interviewer who visited Cowles at his ten-room Palm Beach home in April 1970 described him as "...about six feet tall, and his thin gray hair is combed straight back. His skin is slightly splotch), and freckled, the neck crepey....'I'm getting along,' he said, 'and for a man with a plastic aorta in my heart and a game leg, I'm doing all right.'"
Around 1926, while still in Colorado Springs, Cowles had begun to help his father with the management of the family's financial affairs. He kept in touch with what was happening in the market by subscribing to several investment services that carried tips and other information of varying degrees of reliability. The plethora of publications coming his way finally struck him as "a little wasteful."
He decided to figure out which publication was the best and to subscribe to just that one. In 1928, he started to keep track records on the twenty-four most widely circulated services and continued to do so for four years. That period ran from the height of the great bull market of the 1920s, to the crash of 1929, to the cascading bear market of 1931-32. As the appalling drama unfolded, it seemed to come as a total surprise to the services Cowles was subscribing to. He decided to find out whether the failure was something endemic to the advisory business or just a reflection of the shortcomings of those services.
Ironically, a neighbor of Cowles in Colorado Springs, Robert Rhea, was in the process of reaching exactly the opposite conclusion from Cowles. Rhea, who had been permanently disabled while serving in the aviation branch of the Signal Corps during World War I, was later to emerge as the most famous exponent of Dow Theory. A diligent student of Hamilton's writings, he launched a market letter called "Dow Theory Comment" in mid-1932. The letter put Dow Theory on the map and became so popular that its subscription list reached 6,000, a large number in those days, particularly in view of the depressed state of the stock market and the economy.
Although Rhea made few original contributions to Dow Theory, he is generally credited with having transformed Hamilton's scattered observations into a structured set of ideas. He also traded successfully enough in the market to cover the large medical bills that had accrued during his many years of disability.
Rhea never pretended that market forecasting was simple. He wrote in 1935:
Those who try to profit from the advance and decline of security prices are perplexed perhaps 90% of the time. And it seems that perplexity increases with experience....[U]nvarying cocksureness on the part of traders or investors is a badge of incompetence. There is, nevertheless, a time and place for certainty where the market is concerned, but such times and places are few find far between.
Rhea identified two "times and places for certainty." He called the bottom of the great bear market on the exact day it hit its low, on July 8, 1932, and then predicted the top of the market in 1937. We do not know whether his uncanny forecasting abilities would have continued into the future, because he died in Kansas City in 1939.
Meanwhile, in 1931, Alfred Cowles had set out on his own quest to determine whether stock prices are predictable. His achievements were noteworthy in his own time, and few scholars of any era have been as thorough, as creative, and as helpful to others. The amateur converted himself into a distinguished professional.
Cowles knew what he wanted to do but was uncertain about how to go about it. He consulted his friend Charles Boissevain, a Dutch biochemist with mathematical training who was chief of research at the Colorado Foundation for Research in Tuberculosis, where Cowles was a director and treasurer as well as a patient. Boissevain must have been a colorful and stimulating companion. At one time the champion sculler of Holland, he suffered from both tuberculosis and asthma and had come to Colorado for relief. A contemporary described Boissevain in these words: "He had a brilliant mind and knew what research was all about. Just one caveat though: Webb [the head of the foundation] would have to take care to keep Boissevain on the track. He had so many ideas, so much scientific curiosity, that he might be prone to start up too many hares and not all of them in the tuberculosis field."
Boissevain referred Cowles to Harold Davis, a professor of mathematics at Indiana University who shared Cowle's interest in economics and statistics.
Cowles asked Davis whether it would be possible to compute a mathematical procedure called linear regression with twenty-four variables, an unusually large number. Davis replied that he could not imagine why anyone would want to perform a regression with that many variables, but he helped Cowles acquire a Hollerith machine, IBM's most advanced punch-card n sculler of Holland, he suffered from both tuberculosis and asthma and had come to Colorado for relief. A contemporary described Boissevain in these words: "He had a brilliant mind and knew what research was all about. Just one caveat though: Webb [the head of the foundation] would have to take care to keep Boissevain on the track. He had so many ideas, so much scientific curiosity, that he might be prone to start up too many hares and not all of them in the tuberculosis field."
Boissevain referred Cowles to Harold Davis, a professor of mathematics at Indiana University who shared Cowle's interest in economics and statistics.
Cowles asked Davis whether it would be possible to compute a mathematical procedure called linear regression with twenty-four variables, an unusually large number. Davis replied that he could not imagine why anyone would want to perform a regression with that many variables, but he helped Cowles acquire a Hollerith machine, IBM's most advanced punch-card computer in the early 1930s. Despite Davis's skepticism, he helped Cowles to perform the necessary calculations.
Davis also urged Cowles to get in touch with the Econometric Society, an organization established two years earlier to encourage scholars interested in combining the science of mathematical statistics with economics. Davis was confident that Cowles would find the guidance he was seeking from among the society's membership of about a hundred distinguished economists and mathematicians. With Cowles's still ample fortune in mind, Davis mentioned that the society was short of funds and could afford only occasional small meetings and that the members were eager to publish a journal that would bring their work to the attention of other scholars in their own and related fields.
Cowles immediately wrote to Professor Irving Fisher of Yale, President of the Econometric Society and an old friend of Cowles's father from their undergraduate days at Yale. Like Cowles, Fisher had suffered from tuberculosis in his youth and managed to survive a long stay in a sanitarium. He emerged as a health fanatic and, in particular, as a passionate crusader against alcohol and tobacco.
Fisher had won worldwide reputation as a theoretician for his work on interest rates and statistical innovations. Despite his well-justified fame, his attempts to forecast the stock market had given him a different kind of reputation. On October 15, 1929, just a few days before the Great Crash, he made what John Kenneth Galbraith refers to as his "immortal estimate" that "Stock prices have reached what looks like a permanently higher plateau." That was not bad enough. Fisher went on to say, "I expect to see the stock market a good deal higher than it is today within a few months." On October 21, the day Hamilton published "The Turn in the Tide," Fisher welcomed the ominously weakening market, describing it as "a shaking out of the lunatic fringe." Fisher subsequently lost his substantial fortune, which had been acquired partly from a wealthy wife and partly from an innovative filing system he had developed and marketed.
Fisher was overjoyed to receive Cowles's letter, in which Cowles offered to finance the publication of the Society's journal and the establishment of an organization to promote and publish econometric research. Fisher immediately telephoned Charles Roos, a Swedish economist who was another leader of the Econometric Society. Roos was so incredulous that he asked Fisher whether the letter might have been sent by a crank.
A short time later, Fisher, Roos, and Cowles met at Fisher's home in New Haven. Cowles proposed an initial budget of $12,000 a year -- about $90,000 in 1990 purchasing power -- and promised to provide more if the econometric research drew a response from people outside its immediate field of interest. In an interview many years later, Cowles described himself in his relationship to the Society as "I suppose, its main angel."
In January 1932, Cowles established the Cowles Commission for Research in Economics in Colorado Springs. Its motto was "Science Is Measurement." The Commission, sponsored and supervised by an advisory council consisting of members of the Econometric Society, remained in Colorado Springs until it moved to Chicago in 1939; under Nobel laureate James Tobin's direction, it later moved to Yale. The Commission was home to Nobel laureate Harry Markowitz in the 1950s and is still home to many other famous scholars.
Plans were also made to establish the new journal, to be called Econometrica. That journal is now nearly sixty years old and commands wide respect among economists, statisticians, and mathematicians. The first issue of Econometrica, which appeared in January 1933, contained an introductory article by the famous Harvard economist and the first president of the Econometric Society, Joseph Schumpeter, as well as a timely paper by Irving Fisher titled "The Debt-Deflation Theory of Great Depressions."
The first fruit of Cowles's own research into market forecasting, an article titled "Can Stock Market Forecasters Forecast?," appeared in the July 1933 issue. A three-word abstract of the article concluded: "It is doubtful."
Cowles analyzed the track records of four sets of forecasters: sixteen leading financial services that furnished their subscribers with selected lists of common stocks; the purchases and sales of stocks made by twenty leading fire insurance companies; a test of the Dow Theory gleaned from Hamilton's editorials in The Wall Street Journal; and the twenty-four publications that had set Cowles off on his quest, including sixteen professional financial services, four financial weeklies, one bank letter, and one investment-house letter.
Cowles had set himself quite a job. He had to review 7,500 separate recommendations by the financial services, all transactions over four years by the insurance companies, 255 of Hamilton's editorials that contained definite market forecasts from 1903 to 1929, and 3,300 recommendations by the financial publications. Cowles's careful and thorough research methods are evident throughout the fifteen pages of the article. In each case, Cowles measured the percentage gain or loss against the gain or loss of the stock market as a whole over the same period.
Only six of the sixteen financial services had achieved any measure of success, and even the record of the best performer "could not be definitely attributed to skill" rather than to pure chance. Performance for the group as a whole was negative relative to the performance of the market as a whole. Results for the fire insurance companies were no better and also "could have been achieved through a purely random selection of stocks."
William Peter Hamilton called the top of the bull market in 1929, but apparently he was lucky to do so. True, the portfolio of an investor who had followed Hamilton's timing recommendations would have done all right in absolute terms. Cowles calculated that the portfolio would have grown nineteen-fold during the years from 1903 to 1929 when Hamilton was making his recommendations, a return that led Robert Rhea to remark, "I for one would not complain at such a gain." But an investor who had simply bought into the market in 1903 and had held on for twenty-six years would have ended up twice as wealthy as an investor who had followed Hamilton's advice. Hamilton made twenty-nine bullish forecasts, of which sixteen turned out profitable, and twenty-three bearish forecasts, of which ten were profitable. These results are about what one could do calling heads or tails on the toss of a coin.
Cowles's conclusion on Hamilton's performance were not well received by his neighbor Rhea, whom Cowles had enlisted as one of live experts to judge each of Hamilton's editorials as a recommendation to buy, sell, or hold. Rhea's riposte in one of the issues of his Dow Theory Comment begins gently by referring to Cowles as "...long a friend of mine...doing a commendable job in proving up on the defects of advisory services generally....The report is a clear-cut, concise, and masterly treatise, and I want to say here that I know that Mr. Cowles intended it to represent an impartial and scientific investigation of the theory."
Then he takes off. He insists that Cowles's test of Hamilton's performance was less than fair. He maintains that Hamilton's editorials were intended to be taken as educational pieces, not as investment advice. Hamilton, Rhea insisted, would never have "incurred brokerage charges by closing his account [and going into cash] whenever he was in doubt about the trend." Furthermore, Hamilton never claimed that forecasting was his occupation; he refrained from discussing the market over long periods and frequently traveled abroad. Rhea points out that Cowles chose to end his test of Hamilton's performance with the day Hamilton died, on December 9, 1929, when the Dow Jones Average was 260, already down by a third from its high but still far from its ultimate low. Hamilton had already announced that a bear market was imminent and had sold some stocks. Rhea declares: "Surely no Dow theory student saw anything resembling the termination of a bear market until June and July 1932, and it is inconceivable that Hamilton would have turned bullish before then."
Rhea goes on to argue that, had Cowles continued his investigation beyond Hamilton's death, he would have found that the capital of the buy and hold investor would have suffered a shrinkage of more than 80 percent before the bear market hit bottom whereas the investor who had followed Hamilton's advice could have sat back comfortably with a pile of cash. On the other hand, an indefinite extension of the test period after 1933 might well have put the buy and hold investor back in the lead over the advice of a market-timing Dow theorist.
The financial publications that Cowles investigated fared no better than Hamilton: "We are enabled to conclude that the average forecasting agency fell [below] the average of all performances achievable by pure chance." In 1928, when an investor in the market as a whole would have earned the enormous return of 44 percent, the ratio of bullish to bearish forecasts by this group was only four to three. In 1931, when the market fell 54 percent, the group made sixteen bullish forecasts to every three bearish forecasts.
In each test, Cowles found that the market as a whole had outperformed the practitioners. He also found that the best of a series of random forecasts made by drawing cards from an appropriate deck was just as good as the best series of actual forecasts. Even more depressing, the worst series of random forecasts was better than any of the worst series of actual forecasts.
In recalling this experience many years later, Cowles observed:
Of course, I got a lot of complaints. Who appointed me to keep track? Also, I had belittled the profession of investment adviser. I used to tell them that it isn't a profession, and of course that got them even madder.
Market advice for a fee is a paradox. Anybody who really knew just wouldn't share his knowledge. Why should he? In five years, he could be the richest man in the world. Why pass the word on?
Cowles could not leave the matter alone. In 1944, he published a new study in Econometrica covering 6,904 forecasts over a period of fifteen and a half years. Once again the results failed "to disclose evidence of ability to predict successfully the future course of the stock market." The bullish forecasts outnumbered the bearish forecast four-to-one, even though stock prices were falling more than half the time between 1929 and 1944. These were the grim conclusions from what Cowles characterized as "a very sober academic and professional report" that mentioned none of the services he analyzed by name: "We didn't want to get down to the level of nasty finger-pointing."
Cowles was a compulsive score-keeper on many topics other than the stock market. His son was kind enough to show me a notebook Cowles had kept some time around 1960, which covered both facts and analysis on such varied topics as these:
Advertising, fraction of GNP
Blindness in US
Bridge Life Masters (Chicagoans, & Chicago women)
Death rates, Scheduled airlines -- Domestic US
Dogs -- most popular breeds
Health service manpower
Painting and rising prices
Palm Beach weather
Yale, Admission to
He must have been a fiendish bridge player. Here is one passage from his notes on the game:
If each of 50 million bridge players in the US plays 200 sessions of 40 deals each, this adds up to 50 million x 200 x 40 = 400 billion hands dealt each year in US. The probabilities of any given hand being dealt with 13 cards of one suit are 0.00000000000156. The chances of a hand with 13 cards of one suit being dealt in the US in any given year, therefore are 400 billion times 0.00000000000156 = 0.624.
And so on, working though the chances of hands with 12 cards of the same suit all the way to hands with 7 cards of the same suit.
Cowles's comprehensive research on investment performance, carefully tested against the laws of chance and deeply respected by his academic colleagues, was to find solid confirmation thirty years later in similar studies carried out at a much higher level of sophistication. Like Cowles's analysis, these studies also were greeted by practitioners with deafening silence, especially as the studies appeared as the go-go years of the 1960s were just beginning to roll.
Cowles made other significant contributions to the field of finance. One of the Cowles Commission's goals was to establish an index "to portray the average experience of those investing in [stocks] in the United States." In 1913, under Cowles's direction and inspired by Irving Fisher's pioneering work in developing such statistical tabulations, the Commission published an index purporting to show
...what would have happened to an investor's funds if he had bought at the beginning of 1871 all stocks quoted on the New York Stock Exchange, allocating his purchases among the individual issues in proportion to their total monetary value, and each month up to 1938 had by the same criterion redistributed his holdings among all quoted stocks.
This meticulous effort required over 1,500,000 worksheet entries and more than 25,000 hours on Cowles's primitive Hollerith computer. In addition to earnings, dividends, and composite monthly values based on the averages of high and low prices each month -- monthly closing prices were unavailable at that time -- the Commission provided 59 subcomponents classified by industry membership, dividend yields, and ratios of earnings to prices.
Conceptually, the Cowles Commission indexes are far superior to the Dow Jones Averages. The Dow Jones data are derived simply by adding up the prices of the individual components and dividing by the number of components -- 11 in the early days and now 30 for the Industrials, 20 for the Transportation Average, and 15 for the Utilities.
This scheme gives rise to many complications. The impact of any given stock on the average is dependent, not on the size of the company or its value on the exchange, but simply on the random chance that its price happens to be high or low. A 10 percent change of five points in a $50 stock would have five times as much effect as a 10 percent change of one point in a $10 stock. When a stock splits and the price per share falls proportionately, the total value of the stock in the marketplace is unchanged, but the divisor in the average must be revised in order to maintain continuity. Finally, although the Dow Jones Averages have always been broadly representative of the market, they cover only a segment of it; the Cowles coverage in 1933 included about 97 percent of the market value of all stocks quoted on the New York Stock Exchange and is still, in its present-day incarnation as the Standard & Poor's Composite (also known as the S&P 500 index), much greater than the coverage represented by the Dow Jones Averages.
Why, then, in view of their statistical limitations, have the Dow Jones Averages survived as the measure of the market? Just about everyone was aware that the Dow Jones Industrial Average fell by 500 points on October 19, 1987, but who can recall the number of points lost on the S&P 500 index, assuming that anyone even bothered to notice at the time?
The answer lies in computing power. Until the arrival of high-speed, inexpensive computing in the 1960s, up-to-the-minute publication of the Cowles/Standard & Poor's indexes was impossible. Up to that time the cumbersome process of multiplying the latest prices of hundreds of stocks by the number of shares outstanding limited their publication to once a month. By contrast, the Dow Jones Averages require nothing more than adding a few prices and dividing by a preassigned number -- a job that can be done on a scrap of paper in a minute or less. So, although today the Standard & Poor's data are in much wider use than they were in earlier times, the Dow Jones figures have been the only timely measures available throughout most of stock-market history. Habits die hard.
Investors cling to another stubborn habit: They continue to heed market forecasters, Bachelier and Cowles to the contrary. Cowles was wise enough to understand why this should be so -- and sufficiently self-aware to recognize why he could not join in the fun:
Even if I did my negative surveys every five years, or others continued them when I'm gone, it wouldn't matter. People are still going to subscribe to these services. They want to believe that somebody really knows. A world in which nobody really knows can be frightening.
I don't come to belief easily. I'm an agnostic married to a Christian Scientist. She's tried to convert me, of course, and I want to believe. But I can't.
Copyright © 1992 by Peter L. Bernstein
Excerpted from Capital Ideas by Peter L. Bernstein Copyright ©1993 by Peter L. Bernstein. Excerpted by permission.
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Introduction: The Revolution in the Wealth of Nations.
PART I: SETTING THE SCENE.
Chapter 1. Are Stock Prices Predictable?
PART II: THE WHOLE AND THE PARTS.
Chapter 2. Fourteen Pages to Fame.
Chapter 3. The Interior Decorator Fallacy.
Chapter 4. The Most Important Single Influence.
PART III: THE DEMON OF CHANCE.
Chapter 5. Illusions, Molecules, and Trends.
Chapter 6. Anticipating Prices Properly.
Chapter 7. The Search for High P.Q.
PAR IV: WHAT ARE STOCKS WORTH?
Chapter 8. The Best at the Price.
Chapter 9. The Bombshell Assertions.
Chapter 10. Risky Business.
Chapter 11. The Universal Financial Device.
PART V: FROM GOWN TO TOWN.
Chapter 12. The constellation.
Chapter 13. The Accountant for Risk.
Chapter 14. The Ultimate Invention.
PART VI: THE FUTURE.
Chapter 15. The View form the Top of the Tower.
Bibliography and Other Sources.
Posted January 21, 2013
Posted January 21, 2013
Posted January 21, 2013