Learning From Experience in the Stock Market

Abstract

We study the dynamics of a Lucas-tree model with finitely lived agents who "learn from experience." Individuals update expectations by Bayesian learning based on observations from their own lifetimes. In this model, the stock price exhibits stochastic boom-and-bust fluctuations around the rational expectations equilibrium. This heterogeneous-agents economy can be approximated by a representative-agent model with constant-gain learning, where the gain parameter is related to the survival rate.

Keywords: learning from experience, OLG, assett pricing, bubbles, heterogeneous agents

JEL Classification: G12, D83, D84