Who are you fooling?

"The first principle is that you must not fool yourself - and you are the easiest person to fool."

That was said by the great physicist Richard Feynman in a speech at Caltech in 1974. He meant it in the context of science and scientists, but this is just as true of any field, even remotely resembling research and analysis of any kind. Indeed, it's true in investment research, whether done professionally or for one's self.

What exactly did Feynman mean by this statement? He meant that when we form an idea or a hypothesis, our mind gets convinced by it and starts automatically getting biased towards it. Whether we are conscious of it or not, we start believing in evidence favouring our belief and start discounting proof against it. Maybe our belief is correct or maybe it's not. However, the strength of our belief has nothing to do with its correctness. It's entirely possible to be utterly convinced of something that is completely false and to be able to see any amount of real-world evidence supporting it. This can happen with any belief but especially likely when we have thought of something ourselves. We have a sense of ownership in that belief and defensiveness about it. We can fool ourselves much more easily than others can fool us.

Let me illustrate this point by narrating an episode of an investment analyst who came up with what looked like something interesting and valuable. It was a simple idea to show investors that they should not get too worried if stocks they have chosen fall sharply in a bear market because all stocks that have done well have had big falls (> 50 per cent) at some point. To prove this point, the analyst chose stocks with superlative returns for 10-15 years or more and then, looked at their history. Sure enough, all of them have had some pretty hairy episodes at some point or the other, when the stock price has fallen precipitously. Some of these falls have been during bear markets, but some were independent, stock-specific falls. So, no need to get worried if your stock falls a lot because all good stocks fall sharply at some point or the other. That proves the point, right? Right?

Well, maybe not. The person who has thought of this idea is obviously convinced. However, let's apply the principle of compulsorily arguing against an idea and postulate the opposite. What is the opposite of the above argument? Here it is: instead of starting with a list of stocks that have done well and then seeing if they have fallen badly at some point in the past, how about starting with stocks that have fallen more than 50 per cent at some point and then checking which of those have ended up with great returns over 10-15 years? If you do that, you will arrive at a very different conclusion. It turns out that most stocks that fall sharply at some point stay fallen. These exist in far higher numbers than the successful ones. The history of the stock markets is full of such stocks. Now when you look at the original argument, the flaw is obvious. It suffers from the worst kind of survivorship bias. It starts by eliminating stocks that have done poorly, so obviously, it's bound to end up with a happy conclusion one way or the other.

However, my point is not to critique this particular idea but hold it as an example of finding biases in one's thinking, of trying not to fool the easiest person to fool. I'm sure you've heard of the phrase 'critical thinking'. As it's generally defined, it's essentially about evaluating other people's ideas. That's a lot of fun as looking for flaws in others always is, but perhaps the only kind of critical thinking that is useful and worthwhile is to try and apply it to one's ideas. And if one manages to do that to one's investment ideas, one might end up making more money out of it.