Maybe the reason most investment managers underperform the indexes is that investors, both individual and institutional investors, do a poor job of selecting managers. That’s the thesis of this blog post from Ben Hunt of Salient Investors. He says that most investment decisions are made by engaging in data mining first and them developing a rationale why the results are good. But the scientific method begins with a hypothesis or theory and then uses data to determine whether or not it is valid. It’s interesting reading for all investors.
Frankly and rather unfortunately, your only ability to test many of your hypotheses about fund managers is often going to be through qualitative mechanisms and through live experience. That doesn’t mean you can’t be scientific in your approach. In a perfect world you’d be able to approach a manager without knowing a lick about their performance, have an intellectual conversation about what it is that they do to make money, determine whether it lines up with one of the theoretical ways you think it may be possible to do so, and then evaluate their performance to see if it corroborates that. That’s in a perfect world.
But in an imperfect world, one of the main reasons obsessing over fund managers is one of the Things that Don’t Matter is that almost all practitioners shuffle through dozens of approaches to selecting funds. And almost all those approaches are variants of historical return analysis, or represent historical returns analysis in guise. There’s only one way out of this, and it may be an uncomfortable one:
We’ve got to stop using historical returns analysis for anything other than portfolio fit. Not use it less. Not use it smarter. Those are attempts to stop the wheel. We’ve got to break the wheel.