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For example, if you want to know the probability of a plane crashing, you must know the thousands of instances of planes landing safely, as well as the more attention-grabbing handful that don't. And in considering correlations and causality we must remember instances where one thing happened without the other, as well as when both occurred: I suspect the erroneous fear that the MMR vaccine caused autism arose in part because people looked at a few instances where the administration of the vaccine was followed by a diagnosis of autism and overlooked the millions of instances when it wasn't.

You might think all this should be obvious. But investors make similar mistakes. They neglect the evidential value of what isn't so obvious. For example, star fund managers get lots of attention while thousands of those who underperform do not. This leads people to overestimate the chances of beating the market. And stocks that grow a lot get lots of attention, which leads people to neglect the fact that most stocks, over their lifetimes, under perform cash. This causes people to overestimate their chances of picking a great stock. And Charlie Cai at Liverpool University has shown how investors pay too much attention to companies that have grown a lot while neglecting the tendency for rapid growth to depress profits, with the result that they pay too much for growth stocks.

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