An algorithm may be defined as a formula, process or set of rules that is used to approach or solve a particular problem – usually, though not necessarily, by way of a computer programme. So it is curious that, although algorithms are effective – after all, if they were not, they would not be used in the first place – human beings are apparently disinclined to trust them.
This “algorithm aversion”, notes this Harvard Business Review article, means “even when an algorithm consistently beats human judgement, people prefer to go with their gut”. That interests us here on The Value Perspective because investing in the cheapest stocks over the longer run could be seen as a simple algorithm – and yet, despite its history of outperformance, many investors choose not to buy value.
Another curiosity the article points out is that, while it might seem logical that if people understood “algorithms make better assessments in a wide range of contexts”, they would trust them more, the opposite is in fact the case. “Seeing how algorithms perform makes things worse,” it observes, “because it means seeing the algorithm occasionally make a mistake.”
So the knowledge an algorithm does not work all the time means people are likely to trust it less than they would a human – even if they are shown the algorithm will still do a better job on average. This seems irrational so why does it happen? Well, on questions of irrationality, we often turn to behavioural finance for guidance and one possible answer does immediately suggest itself.
Overconfidence in one’s ability is a behavioural classic, with a commensurately classic illustration being the 1980s study that found more than 75% of participants rated themselves among the top 50% of all drivers in terms of skill and safety. Coincidentally, one of the comments at the end of the online version of the Harvard Business Review article echoed the themes of both confidence and cars.
“I am not sure it is a matter of trusting algorithms too little but rather trusting ourselves too much,” suggested the contributor. “As an example, I can rationally imagine that a self-driving car would be safer than my driving. But I would be reluctant to give up the wheel. However, if choosing between a self-driving car and a friend, I do not feel I would have a strong preference.”
Coming back to investment, value may not work 100% of the time – no strategy does – but, over the longer term, it has been consistently shown to be successful. Yet there are many people who choose not to make use of this ‘algorithm’. Perhaps this is because they have too little confidence in the strategy or too much in themselves, believing – usually erroneously – they can tweak things for the better.
Algorithm aversion or overconfidence? Until more research is done, we can argue and argue about which factor is most at play here. What is not up for debate, however, is that value as an investment style has a long history of outperformance – and that, in turn, is because so few people actually manage to adhere to it properly.