Learning about Risk-Factor Exposures from Earnings: Implications for Asset Pricing and Manipulation
50 Pages Posted: 9 Mar 2021 Last revised: 29 Mar 2021
Date Written: March 8, 2021
When valuing a firm, investors must assess not only its expected future cash flows but also the systematic risk inherent in these cash flows. In this paper, we model the process by which investors may learn about firms' betas from earnings and how this learning process affects the relationship between earnings, announcement returns, and expected future returns. The model's main predictions are: (i) earnings response coefficients vary with macroeconomic conditions and are lower in upswings than downturns; (ii) earnings positively and negatively predict future returns in economic upswings and downturns, respectively, leading to return autocorrelation; and (iii) real earnings management rises in economic downturns and contributes to systematic risk in the economy. These predictions are directly attributable to investors' uncertainty regarding firms' exposures to systematic risk.
Keywords: Earnings betas, aggregate earnings, post-earnings announcement drift, earnings manipulation, return autocorrelation
JEL Classification: G11, G12, M40
Suggested Citation: Suggested Citation