Model Uncertainty in the Cross Section

81 Pages Posted: 14 Sep 2021 Last revised: 28 Dec 2023

See all articles by Jiantao Huang

Jiantao Huang

The University of Hong Kong - Faculty of Business and Economics

Ran Shi

University of Colorado Boulder - Department of Finance

Date Written: September 12, 2021

Abstract

We develop a transparent Bayesian framework to measure uncertainty in asset pricing models. Our framework quantifies the tradeoff between mean-variance efficiency and parsimony for models to attain high posterior probabilities. Model uncertainty is defined as the entropy of these posterior probabilities, which is consistently interpretable even under misspecification due to omitted factors. Empirically, model uncertainty accumulates during major market events, carrying a significantly negative risk premium of approximately half the magnitude of the market. Positive shocks to model uncertainty predict persistent outflows from US equity funds and inflows to Treasury funds.

Keywords: Model Uncertainty, Asset Pricing Factor, Bayesian Inference, Model Selection Consistency, Omitted Factors, Mutual Fund Flows

JEL Classification: C11, G11, G12.

Suggested Citation

Huang, Jiantao and Shi, Ran, Model Uncertainty in the Cross Section (September 12, 2021). Available at SSRN: https://ssrn.com/abstract=3922077 or http://dx.doi.org/10.2139/ssrn.3922077

Jiantao Huang (Contact Author)

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
Hong Kong

Ran Shi

University of Colorado Boulder - Department of Finance ( email )

995 Regent Drive
Boulder, CO 80309
United States

HOME PAGE: http://ranshi.one

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