Net Operating Assets as a Predictor of Industry Stock Returns
48 Pages Posted: 9 May 2006
Date Written: April 2006
Hirshleifer et al. (2004) argue that scaled Net Operating Assets (NOA) measures the extent to which operating/reporting outcomes provoke excessive investor optimism. In this paper, I argue that at least part of the information conveyed by NOA is industry common and cannot be diversified when forming industry portfolios conditioning on NOA for investors with limited attention and investor misperceptions should be related to both the industry and the firm-specific components of NOA. Consistent with this hypothesis, in the 1964-2002 sample, both the cross industry and the within industry components of NOA are strong negative predictors for future stock returns. In contrast, I find that the Accruals effect of Sloan (1996) comes entirely from the industry-adjusted component of Accruals. The industry NOA trading strategy survives the statistical arbitrage test introduced by Hogan et al. (2004), which is designed to distinguish between risk premium and mispricing explanations. I also present evidence that the industry NOA effect cannot be explained by the ICAPM (Khan 2006). Finally, I examine the importance of the time series aggregation property of NOA and its inclusion of investment information, and provide evidence that the industry NOA effect is not driven by the clustering of either new equity issuance or M&A activities within industries.
Keywords: market efficiency, industry returns
JEL Classification: M41, M43, G12, G14
Suggested Citation: Suggested Citation