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.

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