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The traders' concept of the efficient market hypothesis (EMH) is “making money is hard.” This isn't wrong, but it is worth looking at the theory in more detail. Traders are trying to make money from the exceptions to the EMH, and the different types of inefficiencies should be understood, and hence traded, differently.

The EMH was contemporaneously developed from two distinct directions. Paul Samuelson (1965) introduced the idea to the economics community under the umbrella of “rational expectations theory.” At the same time, Eugene Fama's studies (1965a, 1965b) of the statistics of security returns led him to the theory of “the random walk.”

The idea can be stated in many ways, but a simple, general expression is as follows:

A market is efficient with respect to some information if it is impossible to profitably trade based on that information.

And the “profitable trades” are risk-adjusted, after all costs.

So, depending on the information we are considering, there are many different EMHs, but three in particular have been extensively studied:

 The strong EMH in which the information is anything that is known by anyone

 The semi-strong EMH in which the information is any publicly available information, such as past prices, earnings, or analysts' studies

 The weak EMH in which the information is past prices

The EMH is important as an organizing principle and is a very good approximation to reality. But, it is important to note that no one has ever believed that any form of the EMH is strictly true. Traders are right. Making money is hard, but it isn't impossible. The general idea of the theory and also the fact it isn't perfect is agreed on by most successful investors and economists.

“I think it is roughly right that the market is efficient, which makes it very hard to beat merely by being an intelligent investor. But I don't think it's totally efficient at all. And the difference between being totally efficient and somewhat efficient leaves an enormous opportunity for people like us to get these unusual records. It's efficient enough, so it's hard to have a great investment record. But it's by no means impossible.”

—Charlie Munger

Even one of the inventors of the theory, Eugene Fama, qualified the idea of efficiency by using the word good instead of perfect.

“In an efficient market, at any point in time, the actual price of a security will be a good estimate of its intrinsic value.”

—Eugene Fama

There is something of a paradox in the concept of market efficiency. The more efficient a market is, the more random and unpredictable the returns will be. A perfectly efficient market will be completely unpredictable. But the way this comes about is through the trading of all market participants. Investors all try to profit from any informational advantage they have, and by doing this their information is incorporated into the prices. Grossman and Stiglitz (1980) use this idea to argue that perfectly efficient markets are impossible. If markets were efficient, traders wouldn't make the effort to gather information, and so there would be nothing driving markets toward efficiency. So, an equilibrium will form where markets are mostly efficient, but it is still worth collecting and processing information.

(This is a reason fundamental analysis consisting of reading the Wall Street Journal and technical analysis using well-known indicators is likely to be useless. Fischer Black [1986] called these people “noise traders.” They are the people who pay the good traders.)

There are other arguments against the EMH. The most persuasive of these are from the field of behavioral finance. It's been shown that people are irrational in many ways. People who do irrational things should provide opportunities to those who don't. As Kipling (1910) wrote, “If you can keep your head when all about you are losing theirs, … you will be a man, my son.”

In his original work on the EMH, Fama mentioned three conditions that were sufficient (although not necessary) for efficiency:

 Absence of transaction costs

 Perfect information flow

 Agreement about the price implications of information

Helpfully for us, these conditions do not usually apply in the options market. Options, particularly when dynamically hedged, have large transaction costs. Information is not universally available and volatility markets often react slowly to new information. Further, the variance premium cannot be directly traded. Volatility markets are a good place to look for violations of the EMH.

Let's accept that the EMH is imperfect enough that it is possible to make money. The economists who study these deviations from perfection classify them into two classes: risk premia and inefficiencies. A risk premium is earned as compensation for taking a risk, and if the premium is mispriced, it will be profitable even after accepting the risk. An inefficiency is a trading opportunity caused by the market not noticing something. An example is when people don't account for the embedded options in a product.

There is a joke (not a funny one) about an economist seeing a $100 bill on the ground. She walks past it. A friend asks: “Didn't you see the money there?” The economist replies: “I thought I saw something, but I must've imagined it. If there had been $100 on the ground, someone would've picked it up.” We know that the EMH is not strictly true, but the money could be there for two different reasons. Maybe it is on a busy road and no one wants to run into traffic. This is a risk premium. But maybe it is outside a bar where drunks tend to drop money as they leave. This is an inefficiency. There is also the possibility that the note was there purely by luck.

It is often impossible to know whether a given opportunity is a risk premium or an inefficiency, and a given opportunity will probably be partially both. But it is important to try to differentiate. A risk premium can be expected to persist: the counterparty is paying for insurance against a risk. They may improve their pricing of the insurance, but they will probably continue to pay something.

By contrast, an inefficiency will last only until other people notice it. And failing to differentiate between a real opportunity and a chance event will only lead to losses.

Some traders will profit from inefficiencies. Not all traders will. A lot of traders will use meaningless or widely known information. Many forecasts are easy. I can predict the days the non-farm payroll will be released. I can predict what days fall on weekends. I can predict the stock market closes at 4 p.m. eastern time. In many cases, making a good prediction is the easy part. The hard part is that the forecast has to be better than the market's, which the consensus of everyone else's prediction is. For developed stock indices the correlation between the daily range on one day and the next is roughly between 65% and 70%. So a very good volatility estimator is that it will be what it was the day before (a few more insights like this will lead you to GARCH). It is both hard and profitable to make an even slightly better one-day forecast. And whether it is because the techniques that are used are published, employees leave and take information with them, or just that several people have a similar idea at the same time, these forecast edges don't last forever.