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Information overload and disclosure smoothing

Review of Accounting Studies 2019 24(4), 1486-1522 open access
This paper examines whether managers can reduce the detrimental effects of information overload by spreading out, or temporally smoothing, disclosures. We begin by attempting to identify managerial smoothing. We find that when there are multiple disclosures for the same event date, managers spread the disclosures out over several days. Managers are also more likely to delay a disclosure when there has been a disclosure made within the three days before the event date. Finally, managers are more likely to engage in disclosure smoothing when disclosures are longer, the information environment is more robust, firm information is complex, uncertainty is high, and disclosure news is more positive. Our second set of analyses examines whether there are market benefits to disclosure smoothing. Using two different measures of disclosure smoothing, we find that smoothing is associated with increased liquidity, reduced stock price volatility and increased analyst forecast accuracy.

Improving the measures of real earnings management

Review of Accounting Studies 2019 24(4), 1277-1316 open access
Firms often change their operating policy to meet a short-term financial reporting target. Accounting researchers call this opportunistic action real earnings management (REM). They measure REM by the difference between a firm’s costs and those reported by its industry peers. Firms that pursue distinct competitive strategies also display different cost patterns than peers. However, the models that measure REM do not control for differences in competitive strategy. Hence a researcher can misinterpret a cost difference that stems from a firm’s competitive strategy as REM. The researcher would also find a spurious correlation between earnings management and a firm characteristic that varies with competitive strategy. A cause or effect relationship with earnings management could be wrongfully inferred. I suggest improvements in measurement models to avoid misspecification.

Quality minus junk

Review of Accounting Studies 2019 24(1), 34-112 open access
We define quality as characteristics that investors should be willing to pay a higher price for. Theoretically, we provide a tractable valuation model that shows how stock prices should increase in their quality characteristics: profitability, growth, and safety. Empirically, we find that high-quality stocks do have higher prices on average but not by a large margin. Perhaps because of this puzzlingly modest impact of quality on price, high-quality stocks have high risk-adjusted returns. Indeed, a quality-minus-junk (QMJ) factor that goes long high-quality stocks and shorts low-quality stocks earns significant risk-adjusted returns in the United States and across 24 countries. The price of quality varies over time, reaching a low during the internet bubble, and a low price of quality predicts a high future return of QMJ. Analysts’ price targets and earnings forecasts imply systematic quality-related errors in return and earnings expectations.