Structural estimation of behavioral heterogeneity
开发了一个行为资产定价模型，其中交易者因信息摩擦而采用不同策略，利用小群体数据识别并估计结构参数，生成的回报序列与实际数据吻合。
Summary We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit‐maximizing agents switch between trading strategies in response to dynamic market conditions. Owing to noisy private information about the fundamental value, the agents form different evaluations about heterogeneous strategies. We exploit a thin set—a small sub‐population—to point identify this nonlinear model, and estimate the structural parameters using extended method of moments. Based on the estimated parameters, the model produces return time series that emulate the moments of the real data. These results are robust across different sample periods and estimation methods.