In Harvard’s famed Intro to Economics course, which boasts an enrollment size of over 700 students each semester and an alumni list that reads like a Who’s Who of Economics (notables include Fed Chairman Ben Bernanke and Freakonomics author and John Bates Clark Medalist Steven Levitt), students are introduced to the essentials of micro- and macroeconomics in an intuition-heavy, math-light way. In survey fashion, students learn to broadly appreciate concepts ranging from political economy basics and simple game theoretic models as applied to firm competition to the IS/LM model and the Phillips Curve. Students are also taught that markets for goods and services may be inefficient due to such factors as externalities and government policies. Yet, strangely enough, the course devotes just a few short pages to those markets that the future investment banker or commodities trader (ironically, a startlingly high proportion of Harvard students) finds most interesting – equities markets – and states quite frankly that no money can be made therein.
That is, N. Greg Mankiw’s Principles of Economics, in an attempt to introduce the Efficient Markets Hypothesis (EMH) to the fresh-faced economics concentrator, simply posits the hypothesis’s conclusions to the student as true, with little room for discussion. In brief, EMH argues that stock prices very quickly incorporate any information that might cause fluctuation, leaving no discrepancies between current prices and “correct” prices. Because the market is so informationally efficient, there is no opportunity for the investor to predict price movements: security prices should exhibit behavior similar to a random walk. In its heyday in the 1960s, the vast majority of academics and economists accepted this idea as gospel, pointing to its strong theoretical and empirical roots. Led by Eugene Fama, scholars discredited strategies of stock trading that depended upon technical indicators (price movements, trading volume, and other such statistics available from the “chart”), even demonstrating better returns of passive indexed funds (whose strategy relied on matching some broader stock index) than those of actively managed funds led by professional investors. In one of its most striking findings, EMH advocates showed that one could do roughly equally as well or even somewhat better by throwing darts at a list of exchange-traded equities and blindly buying those struck.
Yet somehow, a select group of traders and investors – minds like Warren Buffett, George Soros, Paul Tudor Jones II, and John Paulson – seemed to outperform year after year, with stark margins. Of course, outliers will exist in any statistical distribution, but the consistency with which these elite few beat the market remained an irritating empirical thorn in the side of EMH. Finally, beginning in the 70s and gaining momentum in subsequent decades, the theoretical foundations of EMH began to witness serious challenges. A famous allegory describes an economics student stooping to pick up a $20 bill from the sidewalk when his professor haughtily walks on, claiming that if the bill were actually there – well, it wouldn’t actually be there, because the market would have adjusted, and arbitrage would have eaten it up already!
Fundamentally, EMH relies on perfectly rational actors – investors who will act purely on analysis and not emotion – as well as on the prevalence of arbitrage – that is, the simultaneous buying and selling of cheaper and pricier substitutes or copies of some security to induce price convergence. Those who acted irrationally – termed “noise traders” for their tendency to trade on irrelevant information – were assumed to be randomly irrational, thereby roughly counteracting their own distortions. Fittingly, then, the first challenges to EMH came through research demonstrating irrationality in actor behavior. In Harvard professor Andrei Shleifer’s book Inefficient Markets, he lists several issues with the assumption of actor rationality, including their aversion to risk (first formalized by Kahneman through prospect theory), their faulty judgment skills, and even their erratically changing behavior in the face of the same problem framed differently. Furthermore, Shleifer explains, those who trade randomly do not cancel each other out; rather, they often act in irrational patterns in the aggregate.
Yet the most serious problem with EMH lies in its central tenet of arbitrage: that is, that prices will correct themselves nearly instantaneously as a result of the riskless profit-seeking of savvy arbitrageurs. These “limits to arbitrage,” as Shleifer refers to them, come in various flavors. To begin quite simply, the substitutes required to adjust prices by buying and selling at the same time do not exist or are very difficult to coordinatedly access. Fundamental risk, according to Shleifer, may limit willingness to engage in arbitrage – that is, even if we find close substitutes mispriced, we run the risk of losing everything in the case of firm or sovereign insolvency. And most problematic at all: there is no guarantee over the short run that prices will actually correct. A small volume trader hoping that two illiquid substitute securities will converge may see the price gap widen until she is driven to nil before she witnesses their return to a single price. All this to say that arbitrage – defined as riskless gain – is, in the real world, not at all without risk.
Without a doubt, arbitrage is certainly a dominant profit strategy in highly liquid markets like those trading foreign exchange, oil or precious metals. Yet these are the minority, and even in these arenas, profit is possible through careful analysis. How strange, then, that Ec10 seems to simply accept the existence and effects of efficient markets at face value: that making money through equities research is impossible in the long run. Almost as strange, I’d venture, as dismissing cash on the sidewalk as a mere hallucination.