Working Paper: NBER ID: w27257
Authors: Xiaohong Chen; Lars P. Hansen; Peter G. Hansen
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: Investor Beliefs; Asset Pricing; Behavioral Finance; Statistical Divergence
JEL Codes: E03; E22; E44; G02; G12; G14; G40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Investor beliefs about macroeconomic performance (E66) | Asset prices (G19) |
| Behavioral biases (D91) | Investor beliefs about macroeconomic performance (E66) |
| Model misspecification (C52) | Asset prices (G19) |
| Investor beliefs about macroeconomic performance (E66) | Belief distortions (D83) |