Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
New evidence suggests that individuals “learn from experience,” meaning they learn from events occurring during their lives as opposed to the entire history of events. Moreover, they weigh more heavily recent events compared to events occurring in the distant past. This paper analyzes the implications of such learning for stock pricing in a model with finitely lived agents. Individuals learn about the rate of change of the stock price and of dividends using a weighted decreasing-gain algorithm. As a result of waves of optimism and pessimism, the stock price exhibits stochastic fluctuations around the rational expectations equilibrium. Conditional on the historical path of dividends, the model produces a price–dividend ratio which is in line with the evidence for the last century, except for the “dot-com” bubble in the 1990s.