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.