Investing: The Last Liberal Art (Columbia Business School Publishing)

by Robert G. Hagstrom

At the outset, Charlie mischievously admitted that he was about to play something of a trick on his audience. Rather than discussing the stock market, he intended to talk about “stock picking as a subdivision of the art of worldly wisdom.”1 For the next hour and a half, he challenged the students to broaden their vision of the market, of finance, and of economics in general and to see them not as separate disciplines but as part of a larger body of knowledge, one that also incorporates physics, biology, social studies, psychology, philosophy, literature, and mathematics.

How does one achieve worldly wisdom? To state the matter concisely, it is an ongoing process of, first, acquiring significant concepts—the models—from many areas of knowledge and then, second, learning to recognize patterns of similarity among them. The first is a matter of educating yourself; the second is a matter of learning to think and see differently.

They concluded, in a paper published in 1901, that learning in one area does not facilitate learning in other areas; rather, they argued, learning is transferred only when both the original and the new situation have similar elements. That is, if we understand A, and recognize something in B that resembles A, then we are well on our way to understanding B. In this view, learning new concepts has less to do with a change in a person’s learning ability than with the existence of commonalties. We do not learn new subjects because we have somehow become better learners but because we have become better at recognizing patterns.

According to Holland, innovative thinking requires us to master two important steps. First, we must understand the basic disciplines from which we are going to draw knowledge; second, we need to be aware of the use and benefit of metaphors.

this time in some more detail.5 He first reiterated his basic theme: true learning and lasting success come to those who make the effort to first build a latticework of mental models and then learn to think in an associative, multidisciplinary manner.

“Worldly wisdom is mostly very, very simple. There are a relatively small number of disciplines and a relatively small number of truly big ideas. And it’s a lot of fun to figure out. Even better, the fun never stops. Furthermore, there’s a lot of money in it, as I can testify from my own personal experience.” “What I am urging on you is not that hard to do. And the rewards are awesome…. It’ll help you in business. It’ll help you in law. It’ll help you in life. And it’ll help you in love…. It makes you better able to serve others, it makes you better able to serve yourself, and it makes life more fun.”

The lesson Newton took from Kepler is one that has been repeated many times throughout history: Our ability to answer even the most fundamental aspects of human existence depends largely upon measuring instruments available at the time and the ability of scientists to apply rigorous mathematical reasoning to the data.

Relying on a little-known doctoral dissertation written in 1900 by the French mathematician Louis Bachelier, Samuelson began to weave together a theory of market prices. Bachelier had argued that price changes in the market were impossible to predict. His reasoning was straightforward. “Contradictory opinions concerning market changes diverge so much,” he wrote, “that at the same time instant buyers believe in a price increase and sellers believe in price decrease.” Believing that, on average, neither buyers nor sellers possessed any great insight, Bachelier made a startling conclusion. “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.” Thus, according to Bachelier, “the mathematical expectation of the speculator is zero.”9

complex adaptive systems we must add one more: stock markets. Every complex adaptive system is actually a network of many individual agents all acting in parallel and interacting with one another. The critical variable that makes a system both complex and adaptive is the idea that agents (neurons, ants, or investors) in the system accumulate experience by interacting with other agents and then change themselves to adapt to a changing environment. No thoughtful person, looking at the present stock market, can fail to conclude that it shows all the traits of a complex adaptive system. And this takes us to the crux of the matter. If a complex adaptive system is, by definition, continuously adapting, it is impossible for any such system, including the stock market, ever to reach a state of perfect equilibrium.

The first luminary was Alfred Marshall, the leading economist in Britain (and therefore, some might argue, the world) from the last decade of the nineteenth century until his death in 1924. Marshall’s magnum opus is Principles of Economics, first published in 1890 and revised and expanded seven times afterward. As a comprehensive review of the development of economic thought, it has few equals, and in fact the eighth edition is still used as an important text in many college curricula.

Natura non facit saltum.

Marshall’s audience needed no translation, but today most of us do. “Nature does not make leaps.”

Schumpeter’s dynamic economic process was composed of three principal elements: innovation, entrepreneurship, and credit. At the heart of his theory is the idea that the search for equilibrium is an adaptive process. In that process, innovators are the change agents. All changes in the economic system start with innovation.

steps, Schumpeter’s theory stressed innovative leaps, which in turn caused massive disruptions and discontinuity—an idea captured in Schumpeter’s famous phrase “the perennial gale of creative destruction.”

Unshackling themselves from the classical teachings, the Santa Fe group was able to point out four distinct features they observed about the economy. 1. Dispersed interaction: What happens in the economy is determined by the interactions of a great number of individual agents all acting in parallel. The action of any one individual agent depends on the anticipated actions of a limited number of agents as well as on the system they cocreate. 2. No global controller: Although there are laws and institutions, there is no one global entity that controls the economy. Rather, the system is controlled by the competition and coordination between agents of the system.

3. Continual adaptation: The behavior, actions, and strategies of the agents, as well as their products and services, are revised continually on the basis of accumulated experience. In other words, the system adapts. It creates new products, new markets, new institutions, and new behavior. It is an ongoing system. 4. Out-of-equilibrium dynamics: Unlike the equilibrium models that dominate the thinking in classical economics, the Santa Fe group believed the economy, because of constant change, operates far from equilibrium. An essential element of complex adaptive systems is a feedback loop. That is, agents in the system first form expectations or models and then act on the basis of predictions generated by these models. But over time these models change depending on how accurately they predict the environment. If the model is useful, it is retained; if not, the agents alter the model to increase its predictability. Obviously, accuracy of predictability is a paramount concern to participants in the stock market, and we may be able to achieve broader understanding if we can learn to view the market as one type of complex adaptive system. The whole notion of complex systems

with an example he dubbed “the El Farol Problem.” El Farol, a bar in Santa Fe, New Mexico, used to feature Irish music on Thursday nights. Arthur, the Irishman, loved to go there. On most occasions, the bar patrons were well behaved, and it was enjoyable to sit and listen to the music. But on some nights, the bar was packed with so many people crammed together drinking

and singing that the scene became unruly. Now Arthur was confronted with a problem: How could he decide which nights to go to El Farol and which nights to stay home? The chore of having to decide led him to formulate a mathematical theory he named the El Farol Problem. It has, he says, all the characteristics of a complex adaptive system. Suppose, says Arthur, there are one hundred people in Santa Fe who are interested in going to El Farol to listen to Irish music, but none of them wants to go if the bar is going to be crowded. Now also suppose the bar published its weekly attendance for the past ten weeks. With this information, the music lovers will build models to predict how many people will show up next Thursday. Some may figure that it will be approximately the same number of people as last week. Others will take an average of the last few weeks. A few will attempt to correlate attendance data to the weather or to other activities for the same audience. There will be endless ways to build models to predict how many people will go to the bar. Now let’s say that every lover of Irish music decides that the comfort level in the small bar is sixty people. All one hundred people will decide, using whatever predictor has been the most accurate over the last few weeks, when the limit is going to be reached. Because each person has a different predictor, on any given Thursday some people will turn up at El Farol and others will stay home because their model has predicted more...

In a Santa Fe Institute paper titled “Market Force, Ecology, and Evolution,”

If we go back through the history of the stock market and seek to identify the trading strategies that dominated the landscape, I believe there have been five major strategies, (which in Farmer’s

analogy would be species). 1. In the 1930s and 1940s, the discount-to-hard-book value strategy, first proposed by Benjamin Graham and David Dodd in their classic 1934 textbook Security Analysis, was dominant. 2. After World War II the second major strategy that dominated finance was the dividend model. As the memories of the 1929 market crash faded and prosperity returned, investors were increasingly attracted to stocks that paid high dividends, and lower-paying bonds lost favor. So popular was the dividend strategy that by the 1950s, the yield on dividend-paying stocks dropped below the yield of bonds—a historical first. 3. By the 1960s, a third strategy appeared. Investors exchanged stocks paying high dividends for companies that were expected to grow their earnings at a high rate. 4. By the 1980s, a fourth strategy took over. Warren Buffett stressed the need to focus on companies with high “owner-earnings” or cash flows. 5. Today we can see that cash return on invested capital is emerging as the fifth new strategy.

reallocated—or, in biological terms, there is a change in population. As Farmer notes, “The long-term evolution of the market can be studied in terms of flows of money. Financial evolution is influenced by money in much the same way that biological evolution is influenced by food.”15 Why are financial strategies so diverse? The answer, Farmer believes, starts with the idea that basic strategies induce patterns of behavior. Agents rush in to exploit these obvious patterns, causing an ultimate side effect. As more agents begin using the same strategy, its profitability drops. The inefficiency becomes apparent, and the original strategy is washed out. But then new agents enter the picture with new ideas. They form new strategies of which any number may become profitable. Capital shifts and the new strategy explodes, which starts the evolutionary process again. It is the classic El Farol Problem described by Brian Arthur.

Richard Foster and Sarah Kaplan, from McKinsey & Company, wrote a very important book titled Creative Destruction: Why Companies That Are Built to Last Underperform the Market—and How to Successfully Transform Them.

In her book The Nature of Economies, Jane Jacobs captures the essence perfectly: “A living system makes itself up as it goes along.”18 For that reason alone, I believe that biological systems (stock markets included), unlike physical systems, will never possess a stable mean.

It is interesting to contemplate an entangled bank, clothed with many plants of many kinds, with birds singing on the bushes, with various insects flitting about, and with worms crawling through the damp earth, and to reflect that these elaborately constructed forms, so different from each other, and dependent on each other in so complex a manner, have all been produced by laws acting around us. These laws, taken in the largest sense,

being Growth with Reproduction; Inheritance which is almost implied by reproduction; Variability from the indirect and direct action of the external conditions of life, and from use and disuse; a Ratio of Increase so high as to lead to a Struggle for Life, and as a consequence to Natural Selection, entailing Divergence of Character and Extinction of less improved forms. Thus, from the war of nature, from famine and death, the most exalted object which we are capable of conceiving, namely, the production of higher animals, directly follows. There is grandeur in this view of life, with its several powers, having been originally breathed into a few forms or into one; and that, whilst this planet has gone cycling on according to the fixed law of gravity, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved. (Charles Darwin, The Origin of Species)

titled Confusion of Confusions ([1688] 1996).

Vega’s Confusion of Confusions is easily summarized. In the Second Dialogue, Vega lists four basic principles of trading—as relevant today as they were 325 years ago: The first principle: Never advise anyone to buy or sell shares. Where perspicacity is weakened, the most benevolent piece of advice can turn out badly. The second principle: Take every gain without showing remorse about missed profits. It is wise to enjoy what is possible without hoping for the continuance of a favorable conjuncture and the persistence of good luck. The third principle: Profits on the exchange are the treasures of goblins. At one time they may be carbuncle stones, then coals, then diamonds, then flint-stones, then morning dew, then tears. The fourth principle: Whoever wishes to win in this game must have patience and money, since values are so little constant and the rumors so little founded on truth. He who knows how to endure blows without being terrified by the misfortune resembles the lion who answers the thunder with a roar and is unlike the hind who, stunned by the thunder, tries to flee.

systems. Ilya Prigogine, the Russian chemist, is credited with popularizing self-organization theory. He was awarded the Nobel Prize in 1977 for his thermodynamic concept of self-organization.

new food source. At the beginning, the search for food is a random process, with ants starting out in many different directions. Once they locate food, they return to the nest, laying down the pheromone trail as they go. But now comes the very sophisticated aspect to collective problem solving: the colony, acting as a whole, is able to select the shortest path. If one ant randomly finds a shorter path between the food source and the nest, its quicker return to the nest intensifies the concentration of pheromone along the path. Other ants tend to choose the path with the strongest concentration of pheromone and hence set off on this newly discovered short path. This increased number of ants along the trail deposits even more pheromone, which further attracts more ants until this path becomes the preferred line. Scientists have been able to demonstrate experimentally that the pheromone-trail behavior of the ant colony solves for the shortest path. In other words, this optimal solution is an emergent property of the collective behavior of the ant colony.

isolated individual.”6 Who is right? The answer lies in an outstanding book titled, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations. Written by James Surowiecki,

remained was the distilled information. According to Surowiecki, the two critical variables necessary for a collective to make superior decisions are diversity and independence.

and Think Twice: Harnessing the Power of Counterintuition, tells us “information cascades (which can lead to diversity breakdowns) occur when people make decisions based on the actions of others rather than on their own private information. These cascades help explain booms, fads, fashions, and crashes.”