Occam’s Razor is a cornerstone of the social sciences, and for financial economists it is almost an article of faith. The principle is named after William of Ockham, a 14th-century monk. It holds that the simplest explanation for any phenomenon is the best. Financial analysts today live in fear of “overfitting”: producing a model that, by dint of its complexity, maps onto existing data well, while predicting the future poorly. Now, though, Ockham is on trial. New research suggests that, when it comes to big machine-learning models, parsimony is overrated and complexity might be king. If that is true, the methods of modern investing will be upended.
