Stock market efficiency
Economists have used behavioural economics to explain a number of interesting findings from the stock markets, such as:
• The tendency for stock prices to increase in January.
• The tendency for stock prices to fall in October.
• The observation that stock returns are often slightly lower on a Monday than on the preceding Friday.
But you don’t need to be a hardcore entrepreneur to spot an opportunity here. If stock prices have a tendency to increase in January, and if this is public information, why don’t people simply buy shares in December? The Achilles heel of behavioural economics is that although it provides an explanation for some historical events, it is difficult to utilize as a profitable strategy. And so perhaps markets aren’t “efficient”, but if there is no systematic way to profit from their inefficiency, it is as if they were efficient.
I don’t believe that the EMH is completely correct, but I do think it’s an excellent rule to live by. Here’s how I would classify those who have in fact beaten the market:
When we talk about “skill”, we really mean interpretation. This is what successful traders will claim is driving their success. They receive the same information as other people, but they are better able to understand what it means. Or as one successful trader told me, “price action is like music, whereas economic data is just the component notes”. Some traders have a better ear than others.
Better interpretation helps, but this counts for nothing if you don’t act on it before others. If it’s “news” that drives markets, getting the news first is imperative. In the 1920s there was an instance where a Merrill Lynch broker bribed the company that printed copies of Business Week, in order to get their stories before they hit the stands. The fact that people don’t bribe printers any more tells you something about the value of the information in such magazines. But market-sensitive information is available elsewhere. Because data doesn’t travel at infinite speed, there is evidence that having your Bloomberg terminal geographically closer to their servers gives you a slight informational advantage (and indeed this helps to explain why so many financial firms cluster themselves close to the city). A small number of Thomson Reuters clients paid $6,000 per month in order to receive information 2 seconds sooner than the rest of the market
When my Uncle Roy won the Australian lottery, it wasn’t because he was an expert at lottery theory, or indeed quicker at buying a ticket. He was simply lucky, and we can’t discount luck as a source of profit. Even if we see evidence of people that beat the market, it could primarily be down to random effects. Walter Good and Roy Hermansen took 300 students and asked them to guess the outcome of 10 coin tosses. They then recorded the per- formance of 300 mutual fund managers from 1987 to 1996. They looked at the number of years in which those traders were in the top 50% of all fund managers, and compared this to the simulated ability of students to guess the flip of the coin. The outcome was identical.58 And therein lies the problem – it is incredibly difficult to distinguish between better skill and luck.
A separate way in which it may be possible to stay ahead of the market, without having an interpretative, informational or indeed luck advantage, is if your actions aren’t independent of how the market moves. It may well be the case that other market partic- ipants watch your behaviour (and this may or may not be based on a previous interpretative, informational or luck advantage), and follow suit. If an “oracle” suggests people buy a share, and people do so, it will become a self-fulfilling prophecy. He is ahead of the market purely on account of the market’s willingness to follow.
In this lesson we have been open-minded about the extent to which behavioural economics contradicts the assumptions of standard economics, and tried to see how managers can benefit from being able to see them at work. And the implications for the finance industry are enormous.
But despite these examples of anomalies, they cannot generate a theory that can be profitably applied. After costs, the average investor cannot beat the market. We do not have access to any better estimate of the underlying value of an asset than the market price. Not from historically good traders, and certainly not from regulators.
What this suggests is that rationality, and perfect knowledge are not necessary conditions for efficient markets. Indeed markets are institutions that convert people’s “irrational” beliefs into “rational” outcomes. The greater the degree of “irrationality”, the greater the need for processes that generate the coordination of plans. Behavioural economics doesn’t undermine the case for markets; it strengthens it.