Individual Expectations and Aggregate Behavior in Learning-to-Forecast Experiments

Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations and individual forecasting behaviour in recent learning-to-forecast laboratory experiments with human subjects (Hommes et al. 2007), simultaneously and across different treatments.