Contrarian Investment Strategies

by David Dreman

  In the wake of the financial crisis and the Great Recession, the flaws in economics and EMH have taken on new urgency as millions of people are asking how the economy could have gone so wrong. The questioning is coming not only from major economists and the large numbers of unemployed but from The Wall Street Journal and other bastions of laissez-faire.60

  Most economists, including the world’s most powerful central bankers, had believed for decades that people were rational enough and the markets smooth enough that the whole economy could be reduced to “a handful of equations.” The equations are assembled into mathematical models that attempt to mimic multilevel economic behavior from Washington to Berlin to Beijing. But, as we see, they didn’t work. Instead we are still suffering through the worst financial crisis in modern history. It is certainly not about efficient-market theory alone that the questions are being asked.

  The questioning has gone on for decades. As John Cassidy pointed out in an excellent article in The New Yorker, complex new mathematical theories, such as those of Robert Lucas, Jr., a Nobel Prize winner from the University of Chicago, while causing a generation of novice economists to build ever more complex models, have been discredited, with no agreement on what should replace them.

  Lucas’s work concluded that the Federal Reserve should not actively guide the economy but only increase the money supply at a constant rate.61 The research came under sharp theoretical attack, again because at the core of Lucas’s complex mathematical formulas were untenable simple assumptions such as that supply always equals demand in all markets. (If this were true, we could not have unemployment; the supply of workers would never exceed the demand for them.) Once the supply/demand assumption is dropped, few of Lucas’s conclusions hold up. Commenting on the impracticality of Lucas’s work, Joseph Stiglitz, then the chairman of the president’s Council of Economic Advisors, said, “You can’t begin with the assumption of full employment when the President is worried about jobs—not only this President, but any President.”62

  Economics, traditionally one of the most important of the social sciences, has suffered a self-inflicted decline. Not all in the profession are unaware of this. In 1996, the Nobel Prize in Economics was awarded to two men: William Vickrey, an emeritus professor at Columbia University (for a research paper in 1961), and James Mirrlees, a professor at Cambridge University. Although the popular press extolled Vickrey’s contribution as breaking fresh intellectual ground in fields as diverse as tax policy and government bond auctions, the professor denied the hyperbole. He said, “[It’s] one of my digressions into abstract economics. . . . At best it’s of minor significance in terms of human welfare.”63 When interviewed, he talked instead about unrelated work he had done, which he considered far more important. Complicated statistical analysis is no different in the investment arena, nor should it be, since it’s another branch of economics. Simple assumptions are usually necessary as a platform for abstruse statistical methods. More complex assumptions, although far more descriptive of the real world, do not allow the development of the mathematical analysis that the researchers desire or the academic journals will publish.

  Given the simple assumption of rationality, researchers in the best tradition of the Samuelson Revolution can merrily take off to examine how the totally rational investor will approach markets. They can then use the most complex differential equations or other mathematical methodology to discover new results. Whether the assumptions have the remotest connection to reality is irrelevant. Who cares?

  Thomas Kuhn, in his classic work The Structure of Scientific Revolutions,64 takes a tolerant approach to the problem of paradigm change. It is essential, Kuhn wrote, for scientists to have a paradigm from which to work. A paradigm is the body of theory the scientific community in a field accepts and works within.

  “Paradigms gain their status,” Kuhn argued, “because they are more successful than their competitors in solving a few problems that the group of practitioners has come to recognize as acute.”65 Thus, EMH, in the early years, provided an explanation of prices fluctuating randomly and why technicians could not consistently outperform markets.

  Kuhn also noted that “normal science does not aim at novelties of fact or theory, and when successful finds none.”66 As a paradigm becomes widely accepted, its tools and methods become more deeply rooted in the solution of problems. The accepted tools for broadening the efficient-market paradigm were beta and MPT.

  The goal of normal science is not to question the reigning paradigm but to explain the world as viewed through it. Anomalies that contradict the basic tenets of the paradigm are a serious challenge to it. A paradigm must be able to explain the anomalies, or it will eventually be abandoned for a new one that provides explanations that the first one cannot.

  Thus scientists naturally defend their paradigm. They prefer to believe that all swans are white and do not search for black ones. If scientists find black swans—the anomalies to EMH are such an example—they try to explain them within the theory. A change in a paradigm is a nerve-racking and difficult period with much acrimony.*41

  Its adherents have a vested interest in upholding the validity of the old paradigm, because all their knowledge, experience, and recognition are tied to it. Rejecting their paradigm is often equivalent in a literal sense to rejecting their religion. Kuhn writes that many older scientists will never give up the current paradigm; others will accept parts of it and try to integrate the old with the new. Usually, it takes a new generation of researchers to completely accept a new paradigm. As Paul Samuelson once put it, “Scientific progress is advanced funeral by funeral.”

  And here is a key about why EMH still has so many adherents. Kuhn also brings up a critical point: scientists will never abandon a paradigm, no matter how harsh the criticism, unless they have a more compelling one to take its place that will solve most of the problems the old one could not. It is not surprising, then, that even with the major challenges put to EMH, the hypothesis has not been abandoned. Even though its central tenets have been destroyed empirically, it lives on. Thus, when CAPM was destroyed, the deans of efficient markets stated that there were new measures of risk standing patiently in the wings, with others waiting to be discovered. Or when contrarian value methods were shown to outperform the market, efficient-market researchers claimed that they were riskier. EMH is following the precise course of scientific discovery that Kuhn predicted.

  In Part IV, a new paradigm of market behavior will be offered, based on much we have learned about predictable investor psychology and with strong empirical evidence to back its assumptions. The good news for investors is that it leads to methods that have consistently outperformed markets over time. The bad news is that it is likely to go through an academic Dante’s Inferno for years, perhaps decades, if Kuhn is correct.

  Kuhn also noted that not only is new research not rejected, but its adherents have at times been punished. Thus Giordano Bruno, a Renaissance poet and philosopher, was burned at the stake, and Galileo, as we saw, was imprisoned. The fact that EMH researchers seem intolerant of work that opposes their theory is certainly predicted by the history of scientific discovery. Not surprisingly, there is no forum for dissenting thought, as the academic journals normally do not publish work they consider at odds with their paradigm, including that of knowledgeable Wall Streeters and psychologists.

  Too, EMH adherents are not above attacking research that disagrees with their beliefs. In the early 1980s, for example, both Barron’s and Forbes ran feature stories questioning the efficacy of EMH. The result was an onslaught of critical letters from hundreds of academics that lasted for months. The most common theme was: how could the magazines dare to challenge the work of the distinguished researchers?

  Another disagreeable characteristic of changes in paradigms, demonstrated again with EMH, is the researchers’ use of a number of methods to make the black swans go away. Any criticism of EMH research is met either by silence, if it is not published in major financial
or economic journals, or by dismissal on methodological grounds, as was the case with contrarian strategies until the evidence became too strong. EMH researchers then stated the strategies must be more risky, although they have not yet found a reason why.

  If black swans cannot be ignored, they are attacked. A favorite charge of senior academics defending EMH is data mining, that is, mining only the data you want. This charge, of course, is not used against EMH researchers, who, as we have seen, are now desperately trying to find a risk-reward formula that actually works, although their data mining appears to be on a scale worthy of giant mining concerns such as Rio Tinto or BHP Billiton. Another of their favorite techniques is to criticize methodological flaws, almost down to the misplacement of a semicolon. EMH believers have fortunately never made such errors.

  But the black swans refuse to swim away. They are hatched by many causes, from the shattered assumptions of EMH risk theory to the widespread evidence of investor overreaction to the enormous mispricing in both bubbles and crashes. EMH believers summarily dismiss two different but opposite anomalies—investor overreaction and underreaction—glibly stating that since there is significant evidence on the two, one offsets the other.*42 This is questionable science, since they are two separate anomalies that the researchers cannot explain. Eliminating two separate bodies of evidence because they show opposite results is like stating that 1 + 1 = 0.

  These, then, are some of the hurdles nonbelievers must jump. Some of us have been through this routine numerous times. I turned in my first paper on the superior results of low-P/E strategies in 1977. It was never sent out to a referee, because the editor obviously believed it to be heretical. Only when several of the deans of EMH came out with very similar research fifteen or more years later was it recognized, the credit, of course, going to several of the deans who had originally dismissed such work. Perhaps even worse, the academic journals are, in effect, in the pockets of the major EMH researchers. To publish in the major journals, you must be a true believer or at least a reasonable compromiser. The journals, of course, can make or break the careers of most academics.

  Recall Popper’s statement that only one black swan would be sufficient to kill a theory. Unfortunately for the theorists, there are too many paddling around in the EMH pond to become an endangered species.

  This, then, is the dark side of EMH. But to put it into context, it is not very different from the protest and rancor when any established body of knowledge is threatened by inexplicable facts, and dissenters, at least to my knowledge, are not burned at the stake.

  If I have been somewhat hard on EMH, it is because I cannot accept the manner in which its case has been built, or the widespread damage that its core ideas have brought to markets and, through them, to many millions of people. Although I do not believe the hypothesis, I certainly respect the arduous experimental efforts made by the many researchers in the area. They have finally brought the long-overdue winds of change to Wall Street. Investors who are really interested in how the market works must appreciate these university researchers. Much of the research was necessarily tedious, dull, and time-consuming, but it was essential in building the foundation of a new investment structure.

  Without the thorough measurement of technical and fundamental performance records, Wall Street would have continued in the old, unsuccessful, often disastrous ways, with no impetus toward change. Although it’s obvious that I believe EMH is transitory, it did start the winds of change blowing.

  Armed with the knowledge of the power of psychology to influence our investment decisions, as well as the discovery that the most widely followed investment theory of our time will not help us but work against us, we are now ready to begin to examine strategies that have worked and will continue to work in the difficult markets we currently face.

  Part III

  Flawed Forecasting and Poor Investment Returns

  Chapter 7

  Wall Street’s Addiction to Forecasting

  MAYBE YOU REMEMBER when American folk songs were prominent, or you discovered them on your own and just liked what you heard. You are likely, then, to have heard the name of Woody Guthrie. (And everyone knows his anthem, “This Land Is Your Land.”) He came out of hard times in Oklahoma during the Great Depression, and his songs celebrated the nation’s down and out. His 1939 song “The Ballad of Pretty Boy Floyd” included the line “Some will rob you with a six-gun, and some with a fountain pen,”1 a biting reference to the millions of people who were losing their farms and homes to the foreclosing banks of the time. Now substitute computer spreadsheets for a fountain pen, perhaps with an added stanza or two for some contemporary wrinkles such as collateralized debt obligations, credit default swaps, toxic assets, and exotics, and the lyrics ring true today.

  The national debate on whether there should be more or less regulation and government spending rolls on, with no consensus in sight. It seems that lately, economists can’t agree about much. (See page 155 for more on this.) At any rate, it’s pretty obvious what we’re all wondering: how did the experts ever get us into such a mess?

  By this time you might feel a little as though you’ve just come off basic training on Parris Island or running the New York Marathon. We’ve moved at a brisk pace through some of the important details of why an understanding of investors’ psychology and the intellectual clash over efficient markets is essential to give you the edge when you go into the market wars.

  We’ve detailed the formidable conceptional obstacle course that each presents but that you can come through with flying colors: investor psychology, because it can give you an understanding of how to protect and enhance your savings; efficient-market theory, because, though a failing hypothesis, it can provide deadly results if you’re not aware of the ways it can strike. I hope that the two opening sections have provided you with at least a bare-bones understanding of their importance for what comes next in our psychological investor program.

  In this chapter we will begin to lay out why contemporary investment theory has proved so disappointing over time. It’s not because, as the EMH theorists assume, we are rational automatons, but quite the opposite, because we are human and succumb to human errors—errors that standard investment theory does not take account of.

  Psychology and Major Investment Errors

  Over the last fifty years or so, cognitive psychology has moved in a strikingly different direction from economics theorizing. While economists were embracing a conceptually useful reduction—rational man—psychologists were out to establish an increasingly complex picture of how humans processed information. Spurred by rapid advances in cognitive psychology, sociology, and related fields from the 1980s on, psychologists looked more and more at what differentiated the human mind from machine-based computer logic.

  Even as computers seemed to become capable of mimicking aspects of human cogitation, the fact remains that no computer can rival the human mind for its overall capabilities. However, our mental processes, as we have seen, do not work with the flawless logic of computers, so psychologists have investigated the limits of expert knowledge and information handling. What they found was the often subliminal reasons why even experts fail—and why the rest of us aren’t going to do much better.

  Scores of studies have made it clear that experts’ failure extends far beyond the investment scene. It’s a basic problem in human information-processing capabilities. Current work indicates that our brains are serial or sequential processors of data that can handle information reliably in a linear manner—that is, we can move from one point to the next in a logical sequence. In building a model ship or a space shuttle, there is a defined sequence of procedures. Each step, no matter how complex the technology, advances from the preceding step to the next step until completion.

  The type of problem that proved so difficult to professionals is quite different, however; here configural (or interactive) reasoning, rather than linear thinking, is required. In a configural reasoning problem, the decision m
aker’s interpretation of a piece of information changes depending on how he or she evaluates other inputs. Take the case of a security analyst: when two companies have the same trend of earnings, the emphasis placed on growth rates will be weighed quite differently depending on the outlooks for their industries, revenue growth, profit margins, and returns on capital, and the host of analytical criteria we looked at previously. The analyst’s evaluation will also be tempered by changes in the state of the economy, the interest rate level, and the companies’ competitive environment. Thus, to be successful, analysts must be adept at configural processing; they must integrate and weigh scores of diverse factors, and, if one factor changes, they must reweigh the whole assessment.

  As with juggling, each factor is another ball in the air, increasing the difficulty of the process. Are professionals, in or out of the investment field, capable of the intricate analysis their methods demand? We have seen how difficult this task is and why so many people unconsciously turn to experiential reasoning instead of the rational-analytical methods that are prescribed.