Robust identification of investor beliefs

Xiaohong Chen, Lars Hansen and Peter G. Hansen
Additional contact information
Xiaohong Chen: Department of Economics, Yale University, New Haven, CT 06520
Peter G. Hansen: MIT Sloan School of Management, Cambridge, MA 02142

Proceedings of the National Academy of Sciences, 2020, vol. 117, issue 52, 33130-33140

Abstract: This paper develops a 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 nonlinear expectation function deduced using model-implied moment conditions and bounds on statistical divergence. We illustrate our method with a prototypical example from macrofinance using asset market data to infer belief restrictions for macroeconomic growth rates.

Keywords: subjective beliefs; asset pricing; intertemporal divergence; bounded rationality; large deviation theory (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (9)

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http://www.pnas.org/content/117/52/33130.full (application/pdf)

Related works:
Working Paper: Robust Identification of Investor Beliefs (2020)
Working Paper: Robust Identification of Investor Beliefs (2020)
Working Paper: Robust Identification of Investor Beliefs (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:117:y:2020:p:33130-33140

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