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Robust Identification of Investor Beliefs

Xiaohong Chen (), Lars Hansen and Peter Hansen ()
Additional contact information
Xiaohong Chen: Yale University
Peter Hansen: Massachusetts Institute of Technology - Sloan School of Management

No 2020-69, Working Papers from Becker Friedman Institute for Research In Economics

Abstract: 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.

Keywords: Asset pricing; subjective beliefs; long-term uncertainty; ambiguity aversion; Cressie-Read divergence; generalized empirical likelihood; large deviation theory (search for similar items in EconPapers)
Pages: 61 pages
Date: 2020
New Economics Papers: this item is included in nep-upt
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https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_202069.pdf (application/pdf)

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Journal Article: Robust identification of investor beliefs (2020) Downloads
Working Paper: Robust Identification of Investor Beliefs (2020) Downloads
Working Paper: Robust Identification of Investor Beliefs (2020) Downloads
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