Nº 20-100: Learning (Not) to Trade: Lindy's Law in Retail Traders

We develop a rational model of trading behavior in which the agents gradually learn about their ability to trade, and exit after poor trading performance. We demonstrate that it is optimal for experienced traders to "procrastinate" and postpone exit even after bad results. We embed this "optimal procrastination" in a model of population dynamics with entry and endogenous exit, and generate predictions about the dynamics of various cross-sectional characteristics. We test these population-level predictions using a large client data set of a major Swiss retail broker. Consistent with the model, we find that endogenous exit decisions produce non-trivial and non-monotonic population-wide linkages between performance, exits, and trading experience.