The Mythological Correlation
Forgetting for now why the P/E myth is so easy to buy into, we know people overwhelmingly do believe high-P/E markets predict below-average returns and above-average risk.
But if it were true, you could show some form of high statistical correlation between the claimed cause and result. A statistician will say you can have high correlation between two things out of quirky luck with no causation. But the same statistician will tell you that you can’t have causation without high correlation (unless you run into scientific nonlinearity, which doesn’t happen in capital markets to my knowledge—but you could check on your own with the Three Questions when you’re finished with this book). When a myth is widely accepted, you will find low correlations coupled with a great societal effort to demonstrate, accept and have faith in correlations that don’t really exist.
Investors will root out evidence supporting their favorite myths and create justifications for their belief—factor X causes result Y—while ignoring a mountain of evidence that X doesn’t cause Y at all. Now let’s suppose everyone is of good intent. Still, even with the best of intentions, it’s easy for people to latch onto evidence confirming their prior biases and ignore evidence contradicting their views. Looking for evidence to support your pet theory is human. Accepting evidence to the contrary is no fun at all. This is done in varying ways. One way is to look at a particular time period verifying ...