The Buying Slow but Selling Fast Bias

In this clip professional money manager Ben Griffiths approvingly quotes fellow-trader Larry Williams, “If you get one thing right in your career it is to learn to be a slow buyer and a fast seller”. “If you can master that”, Griffiths continues “you will be well down the way to being a successful manager of money.” Using a huge database of 783 portfolios averaging $573 million in size and covering 4.4 million trades over 16 years, Akepanidtaworn, Di Mascio, Imas, and Schmidt show that professional money managers follow exactly this advice and it is exactly wrong.

Professional money managers do well on their “slow”, buy decisions–somewhat surprisingly, well enough to beat benchmark portfolios. It’s on their “fast”, sell decisions that money mangers significantly underperform the market. Remarkably, the authors show that on average professional money managers would have done better had the chosen what to sell randomly. Why? On their buy decisions money managers put in effort–you can tell they are putting in effort because their buy decisions cannot be explained by simple heuristics based on past returns (such as buy past winners or buy past losers). On their sell decisions, however, managers do appear to follow a heuristic of selling their big past winners or past losers. See the graph where the blue buy decisions are independent of past returns while the red sell decisions show a clear preference to sell positive or negative return outliers. The authors show that this bias reduces return (just as you would expect). When you sell fast you sell what comes to mind quickest, an availability bias, and that’s often a past winner or a past loser even if greater thought would convince you that these are not the best stocks to sell. The sell fast bias, however, is pretty easy to fix. I expect that institutional investors will induce money managers to take a second look at sell decisions, much as computer systems now ask physicians to check branded prescriptions when generics are available.

Addendum: In related news, Deep Mind’s Alpha Star trounced human players of StarCraft II, a game of imperfect information that is much more complicated than chess. Amazingly, Alpha Star made fewer actions per minute than the human players. As with GO the AI developed new long-range strategies never before seen.