Conventional thinking predicts that investment returns and stock prices follow a ‘random walk’ with no predictable pattern – meaning, that they’re determined by today’s news rather than yesterday’s trends. This is known as the ‘efficient markets hypothesis’ (EMH), which states that asset prices fully reflect all available information – and any changes in price reflect the effects of all relevant information as it is released.
A direct implication of EMH is that it is impossible to achieve consistently better returns than an index (colloquially referred to as ‘beating the market’) because all information that could predict performance is already built into the stock prices - prices should only move in a re-action to new information. That is, information that is available to everyone at the same time. Indeed, the ASX, among other securities exchanges, enact regulations to control how a company releases information that could influence its share price. This aims to ensure a level playing field for all investors.
And yet it was observed that in the US between 1904 and 1974, smaller companies returned 3.5% in January and roughly 0.5% in every other month. Further, from 1928 through to 2019, the S&P 500 rose 62% of the time in January (56 times out of 91).1
In behavioural finance, this ‘January effect’ is explained by investors’ seasonal increase in buying stocks. The US tax year follows the calendar year, and the January rise in share prices is down to investors taking advantage of bargains after retail investors realise losses to offset capital gains made elsewhere. The January Effect is a hypothesis, and suggests that the markets are inefficient, as efficient markets would naturally make this effect non-existent.
This is just one observation that behavioural finance theorists use to explain market inefficiencies, highlighting the point that it’s because people are not mathematical equations, and that individuals are influenced by their personal biases. Other commonly used examples include the ‘winner’s curse’, which considers the tendency of the winning bid in an auction to exceed the fair value of the item purchased, and the ‘equity premium puzzle’ that looks to explain the difference between equity and bond returns. And of course, active investors – those who try to perform better than the benchmark – still demonstrate marked variations in performance throughout the year.
We are all human, which means that our behaviour is influenced by our psychology. Some decisions are simple, day-to-day choices, such as what brand of laundry detergent we buy. But others significantly impact our financial well-being, such as whether we buy a particular stock, or how we allocate our money among various investments. Behavioural finance suggests that emotion and deeply ingrained biases influence our decisions more than we consciously recognise, and this makes it hard for us to act truly rationally. And, markets to be truly efficient.
Of course, behavioural finance is not without its critics. For instance, Eugene Fama – the founder of EMH – suggests that even though there are some anomalies for which modern financial theory cannot account for, EMH remains the best model for explaining and predicting economies. The biggest critique of behavioural finance however, is that it is more of a philosophy than an actual science, since there are few, if any, controlled experiments to verify cause to effect.
There are supporters on both sides of the debate. However, more investors are increasingly discussing and using the insights of behavioural finance to improve the ways in which they use EMH to make investment decisions. Behavioural finance should not replace modern finance, but it is an important complement. We often make decisions that are psychologically self-serving, or that take away anxiety, but are not necessarily self-serving from a financial perspective. The tenets of behavioural finance can help us all understand our motivations and weaknesses a little better. This can perhaps help us make better – or at least more rational – investment decisions.
1 Rozeff and Kinney, Capital Market Seasonality: The Case of Stock Returns, 1976. Stephen J Ciccone, ‘January’s Stock Temptation’, The Journal of Behavioural Finance, 2011.
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