Inefficient Markets — Andrei Shleifer on Behavioral Finance and Investor Sentiment

AuthorAthenarium / Posted on

Inefficient Markets — Andrei Shleifer on behavioral finance, risky arbitrage, and investor sentiment

Skip ahead

The gaps in efficiency

Economist Eugene Fama suggested in the 1970s that security prices in an efficient financial market will “always fully reflect the available information”. This tenet of academic finance tells investors that beating the market reliably and consistently is futile. Reflecting a sort of wisdom of crowds, it says that the market know best.

Michael Jensen went as far as to claim that “there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis”. We know, of course, that isn’t saying much. The bar for academic finance isn’t that high. EMH is, as we know today, built on rather rocky foundations.

For starters, the EMH relies on the assumption that investors behave rationally (or that deviations from rationality will cancel out in the aggregate). And even if irrationality were to persist, the EMH assumes that rational arbitrageurs will step in to eliminate mispricing.

We know, however, that many traders do not evaluate their gambles in a way that EMH assumes. They are not rational, utility maximizing, all-knowing calculators. Some will make routine thinking errors, while others find safety in the herd. And this is just the tip of the iceberg.

As Andrei Shleifer notes in Inefficient Markets, while the EMH is a helpful starting point, it is deficient. Finance remains in need of a more complete theory of investor sentiment and market behavior. Behavioral finance, he suggests, may help to fill in the gaps.

Are financial markets efficient?

Market efficiency, Shleifer writes, is “an extreme special case” and unlikely to persist under most market conditions. To see why, it is important to recognise two more things: (1) that there are limitations to arbitrage in real world settings; and (2) a theory of investment sentiment can deviate spectacularly from our descriptions of Homo economicus.

“I’m convinced that there is much inefficiency in the market. These Graham-and-Doddsville investors have successfully exploited gaps between price and value. When the price of a stock can be influenced by a “herd” on Wall Street with prices set at the margin by the most emotional person, or the greediest person, or the most depressed person, it is hard to argue that the market always prices rationally. In fact, market prices are frequently nonsensical”.

Warren Buffett. (1984). The Superinvestors of Graham-and-Doddsville. Columbia Business School Magazine. 

The real limits of arbitrage

Market efficiency appeals to the economist’s intuition because of arbitrage. Naturally, we expect rational, hardworking, profit-seeking capitalists to find, exploit, and correct mispricing in the marketplace. We know, of course, that this is not always the case. Prices can and do deviate from fundamental values.

Shleifer points out, for example, that despite the Royal Dutch and Shell Transport merger in 1907, the “twin-securities” on their respective British and Dutch exchanges showed “enormous deviations from parity, ranging from the relative under-pricing of Royal Dutch by 35 percent to relative overpricing by 10 percent”. 

Here, we have “two fundamentally identical securities”, Shleifer notes, that “sell at different prices — a most basic contradiction to the claim that price equals value”. What’s more, “it [took] about four years for the 30 percent mispricing… to go away”. (Note that this is in reference to prices in the 1980s, well before their unified listing in 2005.)

Substitutes, distortions, and mispricing

So why is arbitrage sometimes slow to respond? For one, arbitrage is risky when perfect or close substitutes do not exist. Arbitrage with imperfect substitutes, after all, must rely on the probabilities of convergence and correction.

As we saw with the rise and fall of Long-Term-Capital-Management (LTCM), mispricing can widen before they close. Noise traders can push prices into absurd ranges. Risk averse arbitrageurs with short horizons and small pockets may find these scenarios untenable.

“Had the failure of LTCM triggered the seizing up of markets, substantial damage would have been inflicted on many market participants,… and could have potentially impaired the economies of many nations… A fire sale may be sufficiently intense and widespread that it seriously distorts markets and elevates uncertainty enough to impair the overall functioning of the economy. Sophisticated economic systems cannot thrive in such an atmosphere.”

Alan Greenspan. (1988). Testimony of Chairman Alan Greenspan. Private-sector refinancing of the large hedge fund, Long-Term Capital Management

Similarly, during full blown panics, investors will withdraw their funds and lenders will recall their loans. “As a consequence,… arbitrageurs can become most constrained precisely when they have the best opportunities”, writes Shleifer.

All of this is a reminder also of the problems we face with measuring and interpreting risk. As Shleifer observes, many investors trade on noise, and so co-movements in stock prices may actually reflect a sort of noise trader risk.  Beta, volatility, and other proxies may not describe market and idiosyncratic risks as well as is traditionally assumed.

Endless dummies and rowdies

Another argument in favor of efficiency is that irrational investors will eventually achieve subpar or negative returns. “Economic selection” they say will eliminate foolish traders, and rational investors will come to dominate. 

Noise traders, however, may add complexity and risk to markets. In a market that fails to return to sanity anytime soon, it may be the arbitrageur who is wiped out first.

Traders may, for example, inspire imitation and positive feedback effects that can help irrational behaviors to persist. What’s more, even if they’re wiped out during the next crash, “a noise trader [is] born every minute”. The supply of rowdies and dummies is seemingly endless.

“Any blanket statements that irrationality will be driven out of the market are surely false”.

Andrei Shleifer. (2000). Inefficient Markets: An Introduction to Behavioral Finance.

A model of investor sentiment

The limitations of arbitrage helps to explain why market inefficiencies can persist. But we need a theory on investment sentiment to understand the direction and reasoning behind mispricing. Shleifer argues that there are two “pervasive regularities” that are inconsistent with theories on market efficiency: underreaction and overreaction.

Efficient market theorists may argue, however, that so-called mispricing are reflective of current information about fundamental risk. Glamor stocks, perhaps, may deserve their premium valuations if they are indeed truly less risky. But there are situations in which prices do appear to move for behavioral reasons alone. In their book Animal Spirits, George Akerlof and Robert Shiller highlight, for instance, the role that confidence multipliers, collective narratives, and money illusions can play in financial markets.

Investors underreact

Similarly, Lauren Cohen and colleagues find evidence of lazy prices and investor inattention in the marketplace. Investors are apparently less responsive today to qualitative news and positive announcements. The study does not attribute the shift to a decline in quality of 10-K reports and announcements, but to the overload in information of recent times.

Indeed, it is not difficult to find examples of price drift following an earnings announcement. To Shleifer, this is evidence that investors are sometimes slow to incorporate meaningful information.

Then there are trading anomalies like the January effect—where it was once possible to earn abnormal returns by concentrating your investments in January every year. Are these statistical aberrations, behavioral biases, or an efficient price? 

Investors overreact

There’s plenty of evidence that investors overreact too. Investors have a tendency to over extrapolate recent trends; and wrongly assume that “this-time-is-different”. Rafael La Porta, likewise, finds evidence of “systematic errors” in analyst stock market forecasts. Their “expectations about future growth in earnings are [usually] too extreme”. 

“More than news seems to move stock prices”, Shleifer adds. One striking example was the Black Monday Crash of 1987, in which the Dow Jones Industrial Average “fell by 22.6 percent… without any apparent news”. Rather, the crash was a product of complex interactions, “structural flaws”, and failed circuit breakers.

Conservatism and representativeness

Two psychological traits may help to explain investor sentiment. The first is conservatism, which says that “individuals are slow to change their beliefs in the face of new evidence”. Conservatism tends to result in underreaction.

The second is a “behavioral heuristic known as representativeness”. It describes our tendency “to view events as typical or representative… and to ignore the laws of probability”. Representativeness tends to generate overreaction.

In this way, underreaction and overreaction are two sides of the same coin. They reflect a sort of inertia in the mental maps that we use to assess the facts and our environment.

As Shleifer writes:

“When investors are hit over the head repeatedly with similar news… they not only give up their old model but, because of representativeness, attach themselves to a new model… As a consequence, investors using the representativeness heuristic might disregard the reality that a history of high earnings growth is unlikely to repeat itself, overvalue the company, and become disappointed in the future when… growth fails to materialize… This series of trials, consistent with experimental evidence, shows a subject underreacting to individual pieces of information, but overreacting to conspicuous patterns.”

Andrei Shleifer. (2000). Inefficient Markets: An Introduction to Behavioral Finance.  

Does it even matter?

It should be clear now as to why the EMH might be a special case of finance, and an unlikely one at that. As we’ve seen, practical limits to arbitrage and the potentialities of investor sentiment can interact together to generate a wider variety of pricing behaviors.

Does it matter? Yes indeed. For starters, overpriced initial public offerings and abnormal returns on share buybacks are not all that surprising when you know that markets are sometimes inefficient. Likewise, capital structure may matter, which contrasts with the propositions made by the Modigliani-Miller Theorem. When markets are inefficient, the choice between debt and equity financing may affect free cash flows.

More importantly, whether right or wrong, theories shape beliefs, and beliefs shape markets. A world in which everyone believes in efficiency will differ from one in which people believe there are opportunities for profit-making. It seems prudent then to understand how people believe and behave. Better theories and models may help us in turn to cultivate a stronger system for all.

As George Soros notes:

“I contend that the slavish imitation of natural science inevitably leads to the distortion of human and social phenomena. Why should social science confine itself to passively studying social phenomena when it can be used to actively change the state of affairs?”

George Soros. (2009). The Soros Lecture at the Central European University.

Sources and further reading

  • Shleifer, Andrei. (2000). Inefficient Markets: An Introduction to Behavioral Finance.
  • Buffett, Warren. (1984). The Superinvestors of Graham-and-Doddsville.
  • Akerlof, George., and Shiller, Robert. (2009). Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism.

Latest posts