The EMH concept asserts that financial markets are “informationally efficient” or that prices on traded assets (such as shares and bonds) already reflect all known information and instantly change to reflect new information. Stock prices, according to this belief, are effectively governed by a random walk. The EMH was refined in 1970 by acknowledging three types of efficiency - “weak”, “semi strong” and “strong.”
The corollary of this theory is that it is impossible to consistently outperform the market by using any information the market already knows, except by luck. A prerequisite of this concept is that collectively investors are rational, dispassionate, readily have access to all public information and will look to take the optimal course of action. Decision making can be broken down into four parts. First, you perceive a situation through a combination of analysis and emotion. Second, you decide what courses of action are available to you. Third, you decide what is in your best interest and then finally you act.
In more recent times, academics studying behavioural finance have led a challenge against EMH, primarily asserting that investors are all subject to an alarmingly large number of behavioural quirks (heuristics). In essence, our computers (brains) have a number of systematic and inbuilt wiring problems. Our software (education) is first class but the mainframe is flawed.
What started out as an arcane study in psychology over half a century ago has now become a mainstream and accepted part of finance. Founding fathers in this area include Nobel prize winning Daniel Kahneman, Amos Tversky and Richard Thaler. As a young psychologist in the Israeli army, Mr Kahneman became aware that people are generally overconfident in their own decisions, even in the face of evidence that their judgement is wrong. He called this phenomenon the “Illusion of validity.” It affects everyone from stockbrokers to doctors.
This can be seen in the success of forecasting. Take inflation forecasts as an example. If you track them against what actually happened, it proves that economists are great lagging indicators. They often tell you what happened in the past because they are highly influenced by the prior number.
Surprisingly and worryingly, meteorologists have gained higher scores than doctors when the former have been given weather patterns and asked to predict the weather and the latter have been given case notes and asked to diagnose the patient. In studies, doctors have put the probability of their being right at 90% but they are actually right just 15% of the time. Being wrong is an accepted part of the meteorologists’ job so their expectations are more realistic.
Investors can exploit such over-confidence as it feeds through into forecasting. For example, investment decisions taken by company managers to support their forecasts often create profit expectations in the stock market that are unsustainable. Investors adopt those unreliable company forecasts to value future profits. These errors are predictable and identifiable and create investment opportunities.
But this mistake is just one of many cognitive errors identified by Kahneman and his frequent collaborator, psychologist Tversky. For more than a decade, the two worked together identifying and listing the ways the human mind systematically misjudges the world around it. For instance, they identified “anchoring bias.” It turns out that whenever you are exposed to a number, you are influenced by that number, intentionally or unintentionally. This is why, for example, the minimum payments suggested on your credit card bill tend to be low. That number frames your expectation, so you pay less of the bill than you might otherwise, your interest continues to grow and your credit card company makes more money than if you had not had your expectations influenced by the low number. Stores use this tactic regularly. What started at £12.99 (not £13) is miraculously reduced to £10.99 and then a jaw dropping £6.99. It must now be good value surely?
Behavioural finance took a leap forward when economist Richard Thaler, then a young professor, co-operated with Kahneman and Tversky during a year at Stanford and the three pooled their combined knowledge on both economics and psychology. In the early 1980s, they published their findings, challenging perceived wisdom of EMH in that people are not entirely rational nor do they always make decisions that are optimal for them.
The main point of contention, says Thaler, was the suggestion that humans are less than perfectly rational when it comes to decision-making.
“Economists literally assume that the agents in the economy are as smart as the smartest economist,” Thaler said. “And not just smart: we’re not overweight; we never over-drink; and we save just enough for retirement. But, of course, the people we know aren’t like that.”
In October 2008, in testimony to Congress about the actions of financial institutions in the lead up to the credit crunch, Alan Greenspan said he was “shocked” that markets behaved as they did. He added: “I made the mistake in presuming that the self-interest of organisations, specifically banks and others was such that they were best capable of protecting their own shareholders and their equity in firms.”
How did so many smart people collectively behave so oddly? How did sophisticated risk models fail so dismally? One explanation is that the EMH world, which may exist in theory, does not exist in practice.
Behavioural finance holds many of the keys to understanding how people behave given complex financial problems and through understanding it investors can exploit the mistakes of other investors. Over-confidence and the consequential fallibility of forecasting, for example, is just one of the aspects of behavioural finance that undermines the EMH. We are emotional beings who often make hasty decisions using our brains that not only encompass hard wiring problems but are swayed by perceptions which may not be reality.
Liontrust fund managers Gary West and James Inglis-Jones seek to exploit behavioural finance and poor forecasting in their investment process – The Cash Flow Solution. Based on US academic evidence, it highlights that investment decision makers are, on average, poor forecasters and yet they are often prepared to bet substantial cash sums that they are right. Such behavioural errors can be exploited both on the long side and on the short side. At extremes, cash flow signals linked to company manager forecasts can provide clues to companies’ likely prospects.
Gary and James, therefore, look carefully at the historic cash flows of businesses and the value that investors in the stock market are prepared to ascribe to them. In their view, the past informs the future, both in terms of the potential for historic cash flows to persist and for businesses to outperform future investor expectations. After three years of applying their process you too might be surprised by the result.
