Abstract
The literature on cash flow or earnings beta is theoretically well-motivated in its use of fundamentals, instead of returns, to measure systematic risk. However, empirical measures of earnings beta based on either log-linearizing the return equation or log-linearizing the clean-surplus accounting identity are often difficult to construct. I construct simple earnings betas based on various measures of realized and expected earnings and find that an earnings beta based on price-scaled expectations shocks performs consistently well in explaining the cross-section of returns over 1981–2017. I also examine the relation between different measures of beta and several firm characteristics that are either theoretically connected to systematic risk or are empirically associated with returns and find evidence in support of the construct validity of an earnings beta based on price-scaled expectations shocks. Overall, the findings suggest that this easy-to-construct earnings beta can be suitable for future researchers requiring a measure of systematic risk.
Highlights
The search for a measure of systematic risk that is priced in the cross-section of returns is an important objective of asset pricing research
0.0% 0.0% 0.2% 0.4% 0.6% 0.8% 1.0% 1.2% Fitted Excess Return outperform betas based on earnings realizations, and betas based on changes in expectations of earnings outperform betas based on levels of expectations
The pricing tests involve 202 portfolios: 25 portfolios sorted by size and book-to-price, 17 industry portfolios, 25 portfolios sorted by operating profitability and investment, 25 portfolios sorted by size and variance, 35 portfolios sorted by size and net issuance, 25 portfolios sorted by size and accruals, 25 portfolios sorted by size and beta, and 25 portfolios sorted by size and momentum
Summary
The search for a measure of systematic risk that is priced in the cross-section of returns is an important objective of asset pricing research. I construct simple earnings betas based on various measures of realized and expected earnings using different scalars and empirically examine their relative performance in explaining the cross-section of portfolio-level and firm-level returns. I contribute to cash flow beta studies by demonstrating that simple earnings betas that use price-scaled expectations shocks seem to perform consistently well in explaining the cross-section of returns. These betas are easier to construct than alternative approaches that either log-linearize returns or log-linearize the clean surplus accounting entity and are a suitable option for future researchers requiring a measure of systematic risk. In a similar spirit, Kelly et al (2019) find that characteristics capture covariances
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