Imagine that you are in a room with colleagues and you are asked to assess whether you are a better, equally good or worse driver than the average person in the room. Just try to give your best estimate, even though you may not know much about the driver capabilities of your colleagues in the room. What would be your answer?

Many studies show that few people will call themselves a ‘worse than average driver’, while a large majority will consider themselves to be ‘better than average’. In other words, most people believe they are better drivers than others. If we replace the word ‘driver’ with the word ‘investor’, the picture is similar: people believe they have better investment skills than others.

This is what psychologists call the overconfidence bias. Most people see themselves as being ‘better than average’; i.e. we have too much self-confidence. This manifests itself in many elements of our decisions: from driving to gambling, and from sports performance to investing. The renowned psychologist Daniel Kahneman also calls this bias ‘the mother of all psychological pitfalls’. Ironically, overconfidence is also something we seem to need to function as human beings: e.g. people less prone to overconfidence seem more likely to suffer from depression.

An important manifestation of the overconfidence bias is in the domain of risk assessments. Let’s say that you are thinking of investing in stocks and that you want to estimate the level of the MSCI World in one year. What do you think the level will be? And what is your assessment of the lower limit of the MSCI World such that there is a 10% chance that the MSCI World will be below the lower limit? And what is your estimate of an upper limit of the MSCI World such that there is a chance of 10% that the MSCI World will be higher than the upper limit? (Hint: write down your answers and compare them to the actual MSCI World level in a year or to econometric estimates).

In such cases, it appears that most investors’ estimates for the lower limit are too high, while their estimates for the upper limit are too low. In other words, we underestimate the risk. Assuming a current MSCI World level of 1600, a reasonable estimate based on econometric techniques (which generally are suitable for estimating volatility) would be a lower limit of approximately 1075 and an upper limit of about 2125. (Were you right?)
Overconfidence has substantial consequences for investors’ behaviour, as it often leads to underestimating risks. Accordingly, overconfident investors tend to take more risks than they should. It could still turn out well though; one can generally expect that taking more risks will lead to higher expected returns (even though this does not seem to apply to all markets). This does not alter the fact that taking too many risks can end (very) badly too (remember Nick Leeson and Jérôme Kerviel).

Overconfidence also leads to having too much confidence in one’s own knowledge. E.g. we are too apt to think that we know which company or asset class is going to outperform the market (remember that there are hundreds of analysts and investment strategists who are all trying to make a similar call). As a result, we tend to trade too quickly and too often; overconfidence leads to a high investment portfolio turnover. Several studies show that this often does not benefit performance, mainly because of higher transaction costs due to the higher turnover.

Can you take action to reduce the impact of overconfidence on your behaviour? Certainly. First of all, be aware of the overconfidence bias. When making investment decisions, ask yourself if your knowledge is really unique and why your knowledge would be better than that of other investors. Secondly, try to improve your estimation skills. Make a weekly or monthly estimation of the range in which an investment could fall in the next week or month and compare your valuations with the actual levels. It is known that this reduces the size of the overconfidence bias at various professional groups. In short, generate experience and train yourself in predicting market prices. Thirdly, focus on reasons why a call could be wrong. This generally helps to reduce underestimation of your risk. ‘Forewarned is forearmed!’


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