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.