Structural estimation of behavioral heterogeneity

Abstract

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.

Empirical Validation of Agent-Based Models ✶ ✶We gratefully acknowledge the very detailed and careful comments by three anonymous reviewers. Very useful feedback and comments have also been provided by Robert Axtell, Herbert Dawid, Cees Diks, and Blake LeBaron.

“…Although the usual goodness-of-fit test, the so-called J-test for equality of empirical and model-generated moments, could always reject the model as the true data generating process for a sample of stock indices and exchange rates, the fit of the selected moments was nevertheless considered satisfactory. Shi and Zheng (2016) consider an interesting variation of the discrete choice framework for switching between a chartist and fundamentalist strategy in which fundamentalists receive heterogeneous news about the change of the fundamental value. A certain fraction of agents then chooses one or the other strategy comparing their pertinent expected profits.…”