Jason Zweig has a great blog post about Dean LeBaron, founder of Batterymarch Financial Management, and pioneer of quantitative investing: the use of statistical analyses rather than human judgment to pick stocks. Batterymarch’s Dean Williams delivered the incredible “Trying Too Hard” speech from 1981, which is required reading if you’re interested in behavioral investment:
I had just completed what I thought was some fancy footwork involving buying and selling a long list of stocks. The oldest member of Morgan’s trust committee looked down the list and said, “Do you think you might be trying too hard?” A the time I thought, “Who ever heard of trying too hard?” Well, over the years I’ve changed my mind about that. Tonight I’m going to ask you to entertain some ideas whose theme is this: We probably are trying too hard at what we do. More than that, no matter how hard we try, we may not be as important to the results as we’d like to think we are.
LeBaron, 80 years old, spoke to Zweig from his home near Sarasota, Fla. He believes that the name of the game for investors has been to make as much money as possible, but from now on, the prime directive will be to “lose as little money as possible.”
If we are in a transition period, then the person who is in the most danger is the one who has recently done well, because he’s done well on things that are about to change.
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In complex systems, the dynamics are predictable but the timing isn’t. It’s like adding a grain of sand one at a time to a pile: You can’t tell when it will collapse, but you know it will.
The highlight for me is this story about one of Mr. LeBaron’s most successful techniques at Batterymarch. Every year he ran a contest to see who could pick the stocks that would perform worst–not best–over the next year. Mr. LeBaron then went out and bought them all–more than 100 at a time–believing that if you can hold on for several years:
You should make enough on the ones that don’t go bankrupt to make up for the ones that do.
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It’s harder than it sounds.
Read Jason Zweig’s blog post about Dean LeBaron.
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One interesting thought is that the reason why that last idea (buying the “worst” stocks selected by the team) works is due to the “Betting Against Beta” effect. As the leverage constrained investor cannot use capital efficiently unless they pick stocks that have a potential downside of 100% then picking stocks that might go out of business is the best (more accurately, most capital efficient) way of investing. In aggregate (i.e. high beta) this doesn’t work but this example does appear to indicate something about improving returns through more capital efficient investments. Just an idea.
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My guess is that it’s an example of mean reversion in the underlying business. The analysts extrapolated out poor fundamental performance, and LeBaron bet against that extrapolation.
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