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Every December the Royal Swedish Academy of Sciences concludes a 16-month nomination and selection process by awarding the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, founder of the Nobel Prize. The Nobel committee recently recognized work on the Efficient Market Hypothesis with a dramatic splitting of the prestigious prize between EMH pioneer Eugene Fama and EMH critic Robert Shiller. (University of Chicago economist Lars Hansen also shares the $1.2 million prize, but we only briefly had the math chops to understand his work back in the late 1980s; we’re told he is very deserving!) This makes now a great time to review EMH, its history, its controversies, where things stand today — and perhaps make our own small contribution to the discussion.

By way of background, we both got our Ph.D.s at the University of Chicago under Gene Fama and consider him one of the great mentors of our lives and an extraordinary man. This might reasonably worry a reader that we are very biased. But for the past 20 years, we’ve also pursued investment strategies we think are at least partly explained by market inefficiencies. We pursued these through the Asian crisis in 1997, the liquidity crisis of 1998, the tech bubble of 1999–2000, the quant crisis of August 2007, the real estate bubble and ensuing financial crisis culminating in 2008 and (for Cliff) the New York Rangers’ not making the National Hockey League playoffs for seven years in a row, starting in 1997. Throughout this experience we have more than once come face-to-face with John Maynard Keynes’s old adage that “markets can remain irrational longer than you can remain solvent,” a decidedly folksier and earlier version of what has come to be known as the limits of arbitrage — a concept we will return to in this article. We could arrogantly describe our investment strategies as a balanced and open-minded fusion of Fama and Shiller’s views but admit they could also be described uncharitably as “risk versus behavioral schizophrenia.”

All of this has put us somewhere between Fama and Shiller on EMH. We usually end up thinking the market is more efficient than do Shiller and most practitioners — especially, active stock pickers, whose livelihoods depend on a strong belief in inefficiency. As novelist Upton Sinclair, presumably not a fan of efficient markets, said, “It is difficult to get a man to understand something, when his salary depends upon his not understanding it!” However, we also likely think the market is less efficient than does Fama. Our background and how we’ve come to our current view make us, we hope, qualified — but perhaps, at the least, interesting — chroniclers of this debate.

Last, we seek to make a small contribution to the EMH conversation by offering what we think is a useful and very modest refinement of Fama’s thoughts on how to test whether markets are in fact efficient. We hope this refinement can help clarify and sharpen the debate around this important topic. Essentially, we strategically add the word “reasonable” and don’t allow a market to be declared efficient if it’s just efficiently reflecting totally irrational investor desires. If you thought that last line was confusing, good. Keep reading.

The concept of market efficiency has been confused with everything from the reason that you should hold stocks for the long run (and its mutated cousins, arguments like the tech bubble’s “Dow 36,000”) to predictions that stock returns should be normally distributed to even simply a belief in free enterprise. This last idea is the closest to reasonable. It is true that there is a strong correlation between those who believe in efficient markets and those who believe in a laissez-faire or free-market system; however, they are not the same thing. In fact, you do not have to believe markets are perfectly efficient or even particularly close to believe in a mostly laissez-faire system. Though it may have implications for many of these things, market efficiency is not directly about any of these ideas.

So what does it really mean for markets to be efficient? As Fama says, it’s “the simple statement that security prices fully reflect all available information.” Unfortunately, while intuitively meaningful, that statement doesn’t say what it means to reflect this information. If the information at hand is that a company just crushed its earnings target, how is the market supposed to reflect that? Are prices supposed to double? Triple? To be able to make any statement about market efficiency, you need to make some assertion of how the market should reflect information. In other words, you need what’s called an equilibrium model of how security prices are set. With such a model you can make predictions that you can actually observe and test. But it’s always a joint hypothesis. This is famously, in the narrow circles that care about such things, referred to as the joint hypothesis problem. You cannot say anything about market efficiency by itself. You can only say something about the coupling of market efficiency and some security pricing model.

For example, suppose your joint hypothesis is that EMH holds and the Capital Asset Pricing Model is how prices are set. CAPM says the expected return on any security is proportional to the risk of that security as measured by its market beta. Nothing else should matter. EMH says the market will get this right. Say you then turn to the data and find evidence against this pairing (as has been found). The problem is, you don’t know which of the two (or both) ideas you are rejecting. EMH may be true, but CAPM may be a poor model of how investors set prices. Perhaps prices indeed reflect all information, but there are other risk factors besides market risk that investors are getting compensated for bearing. Conversely, CAPM may precisely be how investors are trying to set prices, but they may be failing at it because of investors’ behavioral biases or errors. A third explanation could be that both EMH and CAPM are wrong. We will argue later that although the joint hypothesis is a serious impediment to making strong statements about market efficiency, this problem does not have to make us nihilistic. Within reason, we believe we can still make useful judgments about market efficiency.

This framework has served as the foundation for much of the empirical work that has gone on within academic finance for the past 40 years. The early tests of market efficiency coupled efficiency with simple security pricing models like CAPM. The joint hypothesis initially held up well, especially in so-called event studies that showed information was rapidly incorporated into security prices in a way consistent with intuition (if not always with such a formal equilibrium model). However, over time some serious challenges have come up. These can be broadly grouped into two categories: microchallenges and macrochallenges.

The microchallenges center on what are called return anomalies. Of course, even the term “anomaly” is loaded, as it means an anomaly with respect to the joint hypothesis of EMH and some asset pricing model (like, but certainly not limited to, CAPM). Within this category of challenges, researchers have identified other factors that seem to explain differences in expected returns across securities in addition to a security’s market beta. Two of the biggest challenges to the joint hypothesis of EMH and CAPM are value and momentum strategies.

Starting in the mid-1980s, researchers began investigating simple value strategies. That’s not to say value investing was invented at that time. We fear the ghosts of Benjamin Graham and David Dodd too much to ever imply that. This was when researchers began formal, modern academic studies of these ideas. What they found was that Graham and Dodd had been on to something. Stocks with lower price multiples tended to produce higher average returns than stocks with higher price multiples. As a result, the simplest diversified value strategies seemed to work. Importantly, they worked after accounting for the effects of CAPM (that is, for the same beta, cheaper stocks still seemed to have higher expected returns than more expensive stocks). The statistical evidence was strong and clearly rejected the joint hypothesis of market efficiency and CAPM.

The reaction? Academics have split into two camps: risk versus behavior. The risk camp says the reason we are rejecting the joint hypothesis of market efficiency and CAPM is that CAPM is the wrong model of how prices are set. Market beta is not the only source of risk, and these price multiples are related to another dimension of risk for which investors must be compensated. In this case the higher expected return of cheaper stocks is rational, as it reflects higher risk.

The behaviorists don’t buy that. They say the reason we’re rejecting the joint hypothesis of market efficiency and CAPM is that markets aren’t efficient; behavioral biases exist, causing price multiples to represent not risk but mispricing. Prices don’t reflect all available information because these behavioral biases cause prices to get too high or too low. For instance, investors may overextrapolate both good and bad news and thus pay too much or too little for some stocks, and simple price multiples may capture these discrepancies. Another way to say this: The market is trying to price securities according to some rational model like CAPM but falling short because of human frailty. Thus the market is not efficient.

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