Voluntary disclosure, Management forecasts, Information asymmetry, Bid-Ask spreads

[The accounting profession requires that firms disaggregate net income into specific components. Despite the widespread assumption that earnings disaggregation is important for assessing firm profitability, there is little empirical evidence that the classification scheme actually improves profitability forecasts. We analyze accuracy improvements in out-of-sample forecasts of one-year ahead return-on-equity (ROE) to examine the predictive content of earnings disaggregations. The results demonstrate that the classification scheme prescribed by the accounting profession does increase the predictive content of reported earnings. We find forecasting improvements from earnings disaggregation. These improvements go beyond separating extraordinary items and discontinued operations from the other components of earnings. Further disaggregation of earnings (into operating earnings, non-operating earnings and taxes, and special items) improves forecasts of ROE one year ahead.]

Prior research documents mean reversion in firm profitability and growth under the implicit assumption that profitability and growth of all firms revert to a common benchmark at the same rate. However, a large body of academic research suggests that there are systematic interindustry differences (e.g., industry barriers to entry) that differentially affect firm performance based on industry membership. We evaluate the relative forecast accuracy of mean reverting models at the industry and economywide levels and find that industry‐specific models are generally more accurate in predicting firm growth but not profitability.

Accruals are fundamental to financial reporting and are the underlying innovation of accounting. Despite this, accounting research has provided little understanding of how economic forces affect a firm׳s level of accruals and limited guidance for forming expectations of accruals based on ex ante firm characteristics. We consider accruals as a form of investment and examine whether theoretical predictions from a real options-based investment framework provide insight into the relation between accruals and the ex ante expected volatility faced by the firm. Specifically, the theory predicts that higher volatility dampens investment because firms prefer to ‘wait and see’ instead of investing immediately. Consistent with this theory, we document a robust negative relation between year-ahead net working capital accruals and expected volatility. We also predict and find that the negative association between year-ahead net working capital accruals and expected volatility is less pronounced for distressed firms and more pronounced for firms with a longer operating cycle, and that current asset accruals are more sensitive to volatility than current liability accruals. Finally, we find that the residuals from an investment-based expected accrual model outperform those from the widely-used performance-adjusted modified Jones model in identifying companies that just meet or beat analysts’ earnings forecasts. Collectively, our findings suggest that the investment perspective of accruals, and in particular the real options-based investment framework, provide useful insights for forming expectations of accruals.

Mean reversion in profitability and growth is a well-documented phenomenon; however, comparatively less is known about the level of analysis that best captures mean reversion. In this study, we find that analyzing firms by life cycle stage improves the out-of-sample accuracy of profitability and growth forecasts over analyzing firms pooled across the economy and analyzing firms by industry. The improved accuracy is robust to both short-term and long-term forecasts of profitability and growth. We also find that the improvement in accuracy of forecasts from life cycle analyses is greatest for firms in the introduction and decline stages and for firms with greater uncertainty. Finally, we examine market participants' use of life cycle information in forming expectations. We find inefficient use of life cycle information in analyst forecasts, but not in management forecasts. We also find that life cycle forecasts are associated with year-ahead abnormal stock returns.

Prior research reveals that the accrual component of profitability is less persistent than the cash flow component, and that investors fail to fully appreciate their differing implications for future profitability (Sloan 1996). However, accruals are a component of growth in net operating assets as well as a component of profitability. Just as we can disaggregate profitability into accruals and cash flows from operations, we can disaggregate growth in net operating assets into accruals and growth in long-term net operating assets. We find that, after controlling for current profitability, both components of growth in net operating assets—accruals and growth in long-term net operating assets—have equivalent negative associations with one-year-ahead return on assets. This result is consistent with conservative accounting and diminishing marginal returns on investments. We also find that, after controlling for current profitability, the market appears to equivalently overvalue accruals and growth in long-term net operating assets relative to their association with one-year-ahead ROA. Our evidence suggests that the accrual anomaly documented in Sloan (1996) is a special case of what could be viewed as a more general growth anomaly.

Earnings items are typically classified in financial reports based on their persistence and measurement subjectivity. Archival research examines investors' use of persistence and measurement subjectivity classifications for forecasting and valuation. However, this research typically examines only one of these classifications at a time and ignores the potential interactive implications of an earnings item's persistence and measurement subjectivity classifications. We recruited experienced financial analysts to participate in two experiments that examined the effect of measurement subjectivity classifications on analysts' use of persistence classifications when forecasting earnings items. We find that analysts rely less on an earnings item's persistence classification when measurement subjectivity is high relative to when measurement subjectivity is low. We also find that presentation format affects analysts' use of these two classifications. Specifically, we find that the matrix format (i.e., rows display persistence classifications and columns display measurement subjectivity classifications) facilitates analysts' combined use of persistence and measurement subjectivity classifications relative to the sequential format (i.e., the classifications are displayed separately). These findings suggest that archival research could improve its examination of market participants' use of earnings classifications for forecasting and valuation by recognizing that the implications of an earnings item's persistence classification can vary according to the item's measurement subjectivity classification. By also demonstrating how presentation format affects analysts' use of earnings classifications, our study provides further insights into this fundamental issue in accounting research and standard setting.