Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments
通过一个简单的个体学习模型，解释了“学习预测”实验中观察到的三种总体价格行为模式，并发现异质性预期对于描述个体预测和总体价格行为至关重要。
In recent “learning to forecast” experiments (Hommes et al. 2005), three different patterns in aggregate price behavior have been observed: slow monotonic convergence, permanent oscillations, and dampened fluctuations. We show that a simple model of individual learning can explain these different aggregate outcomes within the same experimental setting. The key idea is evolutionary selection among heterogeneous expectation rules, driven by their relative performance. The out-of-sample predictive power of our switching model is higher compared to the rational or other homogeneous expectations benchmarks. Our results show that heterogeneity in expectations is crucial to describe individual forecasting and aggregate price behavior.