Research Publication

December 2020 | Article

Recently published paper in Proceedings of the National Academy of Sciences (PNAS) – “Robust Identification of Investor Beliefs”

Xiaohong Chen, Lars Peter Hansen and Peter G. Hansen

This paper develops a new method informed by data and models to recover information about investor beliefs. Our approach uses information embedded in forward-looking asset prices in conjunction with asset pricing models. We step back from presuming rational expectations and entertain potential belief distortions bounded by a statistical measure of discrepancy. Additionally, our method allows for the direct use of sparse survey evidence to make these bounds more informative. Within our framework, market-implied beliefs may differ from those implied by rational expectations due to behavioral/psychological biases of investors, ambiguity aversion, or omitted permanent components to valuation. Formally, we represent evidence about investor beliefs using a novel nonlinear expectation function deduced using model-implied moment conditions and bounds on statistical divergence. We illustrate our method with a prototypical example from macro-finance using asset market data to infer belief restrictions for macroeconomic growth rates.


Associated Jupyter Code 

Journal: PNAS|Tags: Uncertainty|Export BibTeX >
  title={Robust identification of investor beliefs},
  author={Chen, Xiaohong and Hansen, Lars Peter and Hansen, Peter G},
  journal={Proceedings of the National Academy of Sciences},
  publisher={National Acad Sciences}