Data Truncation Bias, Loss Firms, and Accounting Anomalies

Abstract:     
After performing a Least Trimmed Square procedure at 1%, Kraft, Leone, and Wasley (2006) find an inverted-U relation between Accruals or net operating assets (NOA) and subsequent one-year abnormal returns. They argue that this opposes behavioral explanations for the Accrual and NOA anomalies. We show that the inverted-U relation is a spurious consequence of the truncation bias noted in Kothari, Sabino, and Zach (2005). LTS trimming for these anomalies effectively trims observations by the value of the dependent variable (returns). We show that because returns skewness varies systematically with the accounting predictor, the LTS trimming induces a truncation bias that varies systematically across the accounting predictors. The variation in returns skewness is related to the variation in the incidence of loss firms across the accounting predictors. Among profit firms, which have less skewed returns and so are less subject to the truncation bias, the negative monotonic relation between accounting predictors and subsequent abnormal returns is robust to trimming. Thus, ex post non-random trimming of returns can spuriously induce evidence against either the efficient market hypothesis or behavioral theories. Additionally, this paper shows that the anomalies survive trimming, despite the truncation bias, when a larger set of asset pricing controls and test methods that control for cross-sectional dependence are used.

Keywords: Accruals, NOA, Anomalies, Truncation Bias, Loss, Market Efficiency, Behavioral Finance

JEL Classification: M41, M43, G12, G14

working papers series