Robust Identification of Investor Beliefs

Xiaohong Chen (), Lars Hansen and Peter G. Hansen
Additional contact information
Xiaohong Chen: Cowles Foundation, Yale University, https://sites.google.com/site/xiaohongchenyale/
Peter G. Hansen: MIT Sloan

No 2236, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

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: 63 pages
Date: 2020-05
New Economics Papers: this item is included in nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Related works:
Journal Article: 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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